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Today, video games are a multi-billion-dollar industry, continuously evolving through the incorporation of new technologies and innovative design. However, current video game software content creation requires extensive and often-times ambiguous planning phases for developing aesthetics, online capabilities, and gameplay mechanics. Design elements can vary significantly relative to the expertise of artists, designers, budget, and overall game engine/software features and capabilities. Game development processes are often extensively long coding sessions, usually involving a highly iterative creative process, where user requirements are rarely provided. Therefore, we propose significantly simplifying game design and development with novel Artificial Cognition Architecture real-time scalability and dynamic emotion core. Rather than utilizing more static emotion state weighting emotion engines (e.g. ExAI), we leverage significant ACA research in successful implementation of analog neural learning bots with Maslowan objective function algorithms. We also leverage AI- based Artificial Psychology software which utilizes ACA’s fine grained self-evolving emotion modeling in humanistic avatar patients for Psychologist training. An ACA common cognitive core provides the gaming industry with wider applications across video game genres. A modular, scalable, and cognitive emotion game architecture implements Non-Playable Character (NPC) learning and self-evolution. ACA models NPC’s with fine grained emotions, providing interactive dynamic personality traits for a more realistic game environment and enables NPC self-evolution under the influence of both other NPC’s and players. Furthermore, we explore current video game design engine architecture (e.g. Unity, Unreal Engine) and propose an ACA integration approach. We apply artificial cognition and emotion intelligence modeling to engender video games with more distinct, realistic consumer gaming experiences, while simultaneously minimizing software gaming development efforts and costs.

Emotion intelligence is an important component to enhance the credibility of virtual character's behavior. A virtual character who can perceive and timely to express the appropriate emotions can make the communication between a visual character and a human user more effective and natural. Based on emotional psychology and artificial psychology, this paper simulates the interaction between human emotions, needs and personalities, proposes a new generation method of virtual character's autonomous emotion, and constructs a vision-Based interactive system composed of a facial expression recognition module and a realistic human face model. The results show that the proposed method can make the virtual character produce a more natural emotional reaction in the interaction, and provide an effective method for designing the virtual character's autonomous emotions in the interactive environment.

Cognitive Artificial Intelligence (CAI) is a new perspective in Artificial Intelligence (AI), which brings a new concept of intelligence that is not only limited in the emulation of behavior and ways of how human thinks but also to explore how human's brain grows its knowledge. The development of CAI was started by devising new method that is able to mimick the human's brain ability to perform Knowledge Growing (KG). Based on our long and thorough observation, the knowledge development in human brain is carried out by fusing the information obtained by human sensory organs from the environment. New knowledge is obtained as the time passes by fusing new information with the knowledge already stored in the brain's memory. In this paper we present a method which emulates the mechanism of KG within human brain called A3S (Arwin-Adang-Aciek-Sembiring). The system which uses this method is called as Knowledge Growing System (KGS). We also present an example with real-life data to show the work of A3S in performing KG.

An essential part of modern education is computing. Learning management systems are introduced as an intermediary between a student and a teacher. This paradigm is shifted through reproduction of teacher's and student's intelligent procedures by intelligent agents. The Artificial Intelligence technologies are based on reproduction of principles of human intelligence. Functioning of general Artificial Intelligence is based on principle of double contingency and is impossible without the acquisition of elements of self-consciousness and self-cultivation that can be embodied in Artificial Neural Network. On its basis it is proposed to make intelligent agents on platform IBM Bluemix with IBM Watson technology. These agents in the form of chatbots have to automate the interaction between the student and the teacher within the frames of Moodle learning management system.

Artificial Intelligence is the intelligence shown by machines or software. Artificial intelligence includes reasoning, natural processing language and even various algorithms are used to put the intelligence in the system. In this paper we investigate motivations and expectations for the development of Machine Intelligence. This paper also presents the role of ethics in developing artificial intelligence. In this paper we have compared the new emerging AI scope with the old technologies in various fields and its advantages to the society.

The content of artificial intelligence was to explain its specific concepts and provide examples it uses. Artificial intelligence aims at imitating human behaviour or creative human activity. Theory of artificial intelligence sets its goals. It is related to various scientific disciplines which complement it and in which it searches for possible solutions. Artificial intelligence is constantly discussed by scientists, philosophers as well as laics. They are all interested in two questions — what would happen without it and what it will bring along. The aim of artificial intelligence is to get to know, understand and fully grasp certain processes. These processes are considered manifestations of human intelligence.

This report will first review the breakthrough in the history of human intelligence. Seventy thousand years ago, Homo sapiens achieved “singularity” intellectual breakthrough, the key of this breakthrough is the language-based cognitive revolution they had achieved. Likewise, artificial intelligence also need a language cognitive revolution to achieve a breakthrough. How to break through cognitive intelligence? This report will introduce the breakthrough and initial results in cognitive intelligence IFLYTEK has achieved combined with the research plans, objectives of IFLYTEK Hyper Brain. At the same time, set forth how to use the “ripple effect” to achieve the core technology of artificial intelligence iterative optimization, in the background of the current big data, cloud computing, mobile Internet deeply applied, and to promote a higher level of artificial intelligence.

Due to the characteristics of web data and the change of men-machine interaction mode in the web age, artificial intelligence and information processing encounter new challenges and requirements. The new demand is that information processing has to deal with the meaning or semantics of information. Traditional information processing only treats the form of information rather than the meaning. Artificial intelligence intends to handle information as that of human beings, which makes machines to deal with the meaning or to understand the information. This talk presents new artificial intelligence technologies in the context of text and image processing, as well as intelligent robots. We will discuss how artificial intelligence may face the opportunity and challenge, and what strategy we will adopt to deal with them.

Competitive intelligence deals with the competitive environment of a company. Several studies have been conducted on competitive intelligence domain but there is no empirical work that gives a complete implemented competitive intelligence solution. This paper presents an overview of competitive intelligence studies and highlights the issues towards developing a complete CI solution. A new conceptual model which details the collection phase and incorporates the anticipation of the competitor decisions is proposed. To better solve the CI problem, the paper proposes to integrate the ability of multi-criteria decision aid methods to manage conflicting criteria in a complex environment, with the ability of artificial intelligence in managing and extracting large amount of technical data/information in such a context.

The field of artificial intelligence embraces two approaches to artificial learning. The first is motivated by the study of mental processes and states that artificial learning is the study of mechanisms embodied in the human mind. It aims to understand how these mechanisms can be translated into computer programs. The second approach initiated from a practical computing standpoint and has less grandiose aims. It involves developing programs that learn from past data, and may be considered as a branch of data processing. In this paper, we are concerned with the first approach. Artificial learning is interested in the classification learning that is a learning algorithm for categorizing unseen examples into predefined classes based on a set of training examples. We formulated a computational model for binary classification process using formal concept analysis. The classification rules are derived and applied successfully for different study cases.

Complexity of technology is constantly increasing; for the field of automation this means that economic considerations dictate a need for corresponding measures. Artificial intelligence boasts noteworthy successes in this area; however, its achievements appear modest when compared to the faculties of human intelligence. This paper will demonstrate that a new modeling approach is required via possibilities offered by the mindset and tools of computer technology, thereby demonstrating why a psychoanalytic approach seems sensible and necessary. The paramount goal of the research introduced in the following is a formal approach to describing the human psyche based on the neuro- symbolic and neuronal functional layers. Questions associated with this approach include: To what extent can the psychoanalytic model be confirmed by computer technology and the possibility of simulation? To what extent is an axiomatically developed terminology in psychoanalysis a prerequisite for the better integration of the natural-scientific way of thinking in psychoanalysis? The paper is based on the results of several fundamental research projects within the framework of ARS (Artificial Recognition System) which were funded in part nationally and in part by the EU.

As modern games become more and more sophisticatedgraphically, so does the level of artificial intelligence thatanimates them thus, the larger the game budget, the more workis put into improving the AI. Unfortunately many of these gamesfeature AIs that are standalone and do not communicate witheach other, they do not try to negotiate in order to improvetheir individual standing. The current work focuses on analysingexisting game types in order to establish types of negotiation thatcan be achieved between AI entities. Moreover, an evolutionaryapproach which focuses on achieving negotiation between theseentities and tackles the problem of having multiple negotiationitems with discrete values is presented.

CogPrime, a comprehensive architecture for embodied Artificial General Intelligence, is reviewed, covering the core architecture and algorithms, the underlying conceptual motivations, and the emergent structures, dynamics and functionalities expected to arise in a completely implemented CogPrime system once it has undergone appropriate experience and education. A qualitative argument is sketched, in favor of the assertion that a completed CogPrime system, given a modest amount of experience in an embodiment enabling it to experience a reasonably rich human-like world, will give rise to human-level general intelligence (with significant difference from humans, and with potential for progress beyond this level).

In contrast to intelligence, wisdom is the part of the propositional knowledge part of the background of knowledge that is a mean between two extremes of believing without sufficient evidence and not believing with sufficient evidence. Wisdom may be incorporated in an artificial intelligence system as artificial wisdom (AW). An intelligence system with AW, will learn a collection of activities like a human. AW may be defined as the process of indwelling existing wisdom that is formed from conceiving knowledge. Knowledge is formed on crashing structured information. Indwelling is the process of generating links among different knowledge modules. Links will have strengths that will define the efficiency of the AW. Strengths will depend on the metafunction equivalents of the background of knowledge that are analyzing, synthesizing and imagining, and valuing. These metafunction equivalents are to be set against key temperament characteristics of AW that are `allergy to ambiguity', `conformity', `rigidity', `starved sensibilities' etc.

Affective virtual human is considered to one of the hotspots in the field of virtual human-computer interaction. First, the software platform of the management system has been designed, and the virtual human emotional model has been analyzed. Then, management functions have been carried out or simulated by many technologies. For example, face recognition, speech emotion interactions, text emotion recognition, eye tracking and other technologies. And the management system with emotional virtual human applied on smart home can construct a harmonious living environment, and improve user satisfaction and comfort. Finally, the improvements of the management system are described, to enable better application of human-computer interaction in the harmonious environment.

In this article we have described the result of the ongoing research of artificial intelligence, a new look at the creation of prototype of human brain and propose of new possible scheme of intelligence. Without details, herein, explained principal points, given the short terms of the structure of preparing computer software and some possible elements of artificial intelligence. The article is focused on the development of electronic variation at the decision-making process.

With the advent of artificial general intelligence architectures, comparison between different architectures became more complicated. Small isolated tasks like box stacking, path finding, chess, or collecting objects is sufficient for highly specialized algorithms like the ones used in artificial intelligence. The holistic control systems are designed to cope with rich, dynamic, and complex real world environments and tasks. The approaches used to design these architectures differ in many ways but all share the goal to create human like “intelligence.” Each project uses its own approach to evaluate its success which is usually tightly coupled with the target application. We propose the usage of a simulated virtual world with embodied autonomous agents. These agents should be equipped with control systems from the architectures that should be compared and exposed to situations where their performance is assessed. The situations—or test-cases—have to be designed with tests from psychology in mind. Thus in a top-down design approach, tests from psychology have to be refined and converted such that they can be implemented into the simulation. We discuss different approaches and introduce the use-cases developed for project ARS.

Affective virtual human is considered to one of the hotspot in the field of virtual human-computer interaction. In this paper, the history and status quo of affective virtual human area have summarized. First, the relevant research history and development of affective virtual human-computer interaction at home and abroad is introduced and illustrated. Secondly, by induction the classification of affective model which is the core part of the affective virtual human technology, the characteristics, advantages and limitations of models are introduced and summarized. Then the involved theory and technique based on this field are discussed. Finally, the future of this area is prospected in the summary of the paper.

Artificial intelligence is facing the changes of research program. New research program which is based on the idea of new connectionism should be established. This paper analyzes the dilemma of reductionism and holism existing in artificial intelligence theoretical research, and interprets theoretical basis of research program of new connectionism.

This paper provides a general overview of the interdisciplinary study of cognitive science, specifically the area of the field involving artificial intelligence. In addition, the paper will elaborate on current research for cognitive science artificial intelligence, highlight the importance of this research by providing specific examples of its applications in present society, and briefly discuss future research opportunities for the overlapping fields of cognitive science and artificial intelligence.

This article re-visits the foundation concepts of Computational Intelligence in relation to the established field of Artificial Intelligence and describes an emerging data technology, Formal Concept Analysis, that can contribute to the topic. Technologies from Artificial Intelligence are briefly considered in relation to the need for improved knowledge representation and accessibility rather than more refined reasoning algorithms that operate in restricted domains.

This paper research the application of artificial intelligence in mobile learning. In the first place, this paper analyse the meaning of mobile learning and artificial intelligence, make them clear to people. In the second place, explain the significance of the application of artificial intelligence in mobile learning. This paper introduce five problems in mobile learning. These problems make it necessary to apply artificial intelligence. In the third place, introduce the specific application of artificial intelligence in mobile learning. It include: 1)Mobile Intelligent Teaching Expert System(MITES).2)Mobile Intelligent Decision Support System(MIDSS).3)Mobile Intelligenct Information Retrieval Engine (MIIRE).4)Mobile Intelligent Induct-learning System (MTIS).5)Intelligent Hardware Network (IHN). Finally, looking to the future, there are two main problems about the artificial intelligence in mobile learning:1)Technical problems.2)Development of soft tools.

Artificial intelligence is a comprehensive cutting-edge discipline which is developing, and an important research direction in the fields of science computer and technology. This paper uses the principles and methods of artificial intelligence on the basis of describing the concept and research areas of artificial intelligence, focuses on in-depth analysis and discussion of applicable perspective and development of artificial intelligence in modern physical education technology, and raises the corresponding development strategies to the use of artificial intelligence in modem sports educational technology, in order to provide the theoretical support for the establishment and development of modern physical education technical disciplines.

The artificial intelligence is the important achievement of the development in computer science on the 21st century, which has a wide range of applications in many areas. This paper discusses the definition and nature of artificial intelligence, analyzes of the current research in various fields, sums up the history and present situation of artificial intelligence research and analyzes its development direction.

The improvement of design for a better E-learning system based on cognition and emotion is proposed in this paper. Some theories including cognitive science, artificial emotion, artificial psychology theories and multimedia design principles based on emotion & cognitive theories are used for this design. Then the emotion cognition model of E-learning system is researched and builded. Through comparing retention test and transfer test, three typical student scenarios are defined as E-learning assessment strategies. The customizable learning paths are intelligently adjusted according to students' demonstrated interests, emotional status and learning capabilities by the navigation module in this E-learning design. This E-learning system design will significantly improve the quality of online education and study.

We give an instability result of a problem in artificial intelligence by means of the analysis and computing method.

The purpose of this article is to describes explores ways to solve the difficult problems in the study of the intelligent information retrieval system. This paper first discusses the basic concepts and the structure of the intelligent information retrieval system, the principles of artificial intelligence, the relationship between computer and artificial intelligence, the stage of artificial intelligence research experience, research areas and applications of artificial intelligence, the components and the use of the artificial intelligent information retrieval system in detail. And using the results of the artificial intelligence research, suggests the method to solve the difficulties which are in the areas of natural language understanding, knowledge representation and knowledge acquisition.

Research in automation focuses on systems which are capable of solving very complex tasks and problems. Artificial Intelligence and especially Cognitive Science have brought remarkable successes; however, in some areas the boarders of feasibility and further extension are reached. Compared to human intelligence the range of capabilities of the solutions is still modest. In the following we will argue why we see the necessity to introduce a novel approach for creating models, which possibilities and tools computer engineering can offer, why a psychoanalytical template is considered meaningful, and which open problems could be tackled or even broken through with this approach, respectively. The article is based on comprehensive research results in the course of several research projects including a European one. Involved persons originate from a number of research institutions in Austria, South Africa, and Canada.

This paper attempts to do a research on personalized recommendation in a completely original way-a recommendation based on psychological community. On the basis of concept of psychology and theory of artificial psychology, we provide two methods to quantify personal psychological properties: client remark and Quantity I Theory. The system transforms a direct link between client and recommendable object into an indirect form, building psychological community between them. That is to say, no more do we seek to directly match clients with the objects they might be interested in, instead, the system sets up psychological community containing two attributes - client and recommendable object as a bridge to match the two together.

A method is presented to construct an embodied artificial intelligence. The method grows out of a system for object recognition in artificial vision and relies upon such a capability. Examples from the biosphere are extensively discussed in coming to the method which has, as its central tenet, that all intelligence is fundamentally related to objects. All the aspects needed by an embodied intelligence are developed including consciousness, memory and volition.

This paper reviews the field of artificial intelligence focusing on embodied artificial intelligence. It also considers models of artificial consciousness, agent-based artificial intelligence and the philosophical commentary on artificial intelligence. It concludes that there is almost no consensus nor formalism in the field and that the achievements of the field are meager.

Traditional intelligent CAI (Computer Aided Instruction) pays less attention to emotional cognition. To address this problem, an emotional pedagogical system based on artificial psychology and Agent theories is presented. Student’s emotion is considered as one of the secondary index in two-layer fuzzy comprehensive assessment model to assess study effect. Inference engine outputs the final teaching strategies and teaching suggestions by making reference to the assessment results. Agent achieves teaching goal not only according as cognitive factors but also by perceiving and adapting to student’s psychological state. Pedagogical system based on a double source of emotion and cognition mechanism during assessment and interaction is built to simulate the “man-to-man” classroom's teaching.

Virtual Instruction has triggered profound changes in the field of distance education. However, “teachers” usually ignore the emotional factors of students in VI environment, which will severely harm the quality of learning. Affective Intervention Learning Algorithm (AILA), a novel method for emotional interaction learning in virtual instruction is proposed in the paper, which tracks the affective states of students and implements encouragement strategies appropriately through their learning journey in virtual instruction environment. Finally, an affective intervention learning model based on expression recognition is established to verify its effectiveness. The simulation results demonstrate that AILA is a feasible and effective approach to solving the problem of emotional absence in virtual instruction.

The application of semantic Wikis for user information management in e-business for purpose of Web personalization is investigated in this paper. It presents an enhanced semantic wiki, named UIMwiki, aiming to combine user annotation and artificial psychology in a semantic wiki system. Wiki users in UIMwiki are classified into three groups: end users, expert users and ontologists. There are two ways to maintain user information in UIMwiki for an end user: executing a cognitive query or adding semantic annotations. A user model based on artificial psychology can be built from the cognitive query files by a user model generator. The user model generator gives user model suggestions based on psychology knowledge. The Wiki generator and semantic annotation are also described. UIMwiki considers user's preference information or implicit knowledge in the annotation process, and it makes the personalization more effectively too.

The paper presents a facial expression recognition approach based on wavelet transform features and neural network ensemble classifier for the six basic facial expressions from static images of the CMU-PITTSBURGH AU-Coded Face Expression Image Database. Because the facial expression information are mostly concentrate on facial expression information regions, so the mouth, eye and eyebrow regions are segmented from the facial expression images firstly. Then the low-dimension features using wavelet transform and Karhunen-Loeve transform are acquired. A neural network ensemble classifier based on Bagging is constructed finally. The proposed approach has demonstrated superior performance compared to neural networks. The neural network ensemble based classifier yielded an accuracy of 98.5%; the best accuracy obtained from all other neural network based classification schemes tested using the same database.

This paper proposes an innovative teaching and learning theoretical framework based on psychological incentive mechanism and Artificial Psychology theory. Related works about these two areas will be addressed in section 2. This framework includes three type pedagogical agents, namely the Expert agent, the Mentor agent and the Motivator agent. This framework is intended to create a positive and personalized study environment for the learners with the sufficient consideration to the learnerpsilas emotion ingredient, learnerpsilas personal preference and the appropriate application of the pedagogical psychology. The goal of this framework is to stimulate the learnerspsila internal drive to promote them to be active in the learning process.

Adaptive e-learning system, deal with appropriate personalization and adaptation techniques in order to maximize the effectiveness of learning. Customer preference and personality are going to be more and more important to e-learning. This paper first hopes to explain the grid agent e-learning model, whose main actions including registry, directory and discovery. Through these actions, the managerpsilas agent will find out the suitable learning services. Secondly, to implement the adaptability of the grid agent model, the method of artificial psychology and how to realize adaptive personalized e-learning by this method so that the studentpsilas agent can employ the learning material matched to their own personality type are also emphasized. The experiment data also supported our assumption that the learners may perform better if they use our adaptive grid agent model.

In order to raise study efficiency in distance education, how to realize humanistic solicitude and harmonious emotion interaction between man and machine has become the important subject that should be researched thoroughly. This paper describes the theory and methods of emotional information processing as well as Affective Computing Contents and other related technology. Besides, it presents the FPBDIC Agent Mental Model and the Intelligent Personality Education System Model with techniques in the course of researching on harmonious man-machine emotion interaction system based on software Agent technology.

Emphasizing particularly on emotional interactions, this paper proposes a Web-based, personalized e-learning navigation design, which is composed of emotion modeling based on artificial psychology, image recognition, Web log analysis and knowledge level evaluation based on cognitive psychology. In this paper, eye-sight track and student-computer interaction are presented. Eye-sight track aims at tracking on-line which contents on computerpsilas screen are concentrated on by the learner. Through the interactions between test-pages and learners, their real-time learning interests as well as encountered difficulties in learning process can be identified. By adopting artificial psychology theories and knowledge level-structure evaluation method, each individual studentpsilas knowledge level and knowledge background are evaluated. Then bases on the information fusion with respect to the above attained information, an optimal learning plan or curriculum structure can be provided via the ultimate evaluation result, some constructive suggestions are provided as well. The design will greatly improve the learning efficiency of student and promote human-computer interaction.

Summary form only given. When employing the views of granular computing to the studies of artificial intelligence, it can be seen that there have been various levels of granule existed, system level, element level, and sub-element level, etc., each of which has its own interest of research. As for the system level of granule is concerned, there have also been various views of angle among which structural angle (Structuralism Approach), functional angle (Functionalism Approach) and behavioral angle (Behaviorism Approach) are representatives. Each of the approaches to AI has made progresses and faced problems as well. In this paper, a new approach, named the Mechanism Approach, to the system level of granule in AI research is presented, which focuses on the core mechanism of intelligence formation in general cases. It is discovered that the Mechanism Approach can be implemented via the transformations that are able to converse the information to knowledge and further to intelligence. The new approach is also proven to be able to unify the three approaches mentioned above and thus bring about a unified theory of AI. Both the mechanism approach and the unified theory may make AI research more promising than ever before.

This paper has the objective of describing the structure and placing in a taxonomy the Artificial Adaptive Systems (AAS). These systems form part of the vast world of Artificial Intelligence (AI) nowadays called more properly Artificial Sciences (AS). Artificial Sciences means those sciences for which an understanding of natural and/or cultural processes is achieved by the recreation of those processes through automatic models. In particular, Natural Computation tries to construct automatic models of complex processes, using the local interaction of elementary micro-processes, simulating the original process functioning. Such models organize themselves in space and time and connect in a non-linear way to the global process they are part of, trying to reproduce the complexity through the dynamic creation of specific and independent local rules that transform themselves in relation to the dynamics of the process. Natural Computation constitutes the alternative to Classical Computation (CC). This one, in fact, has great difficulty in facing natural/cultural processes, especially when it tries to impose external rules to understand and reproduce them, trying to formalize these processes in an artificial model. In Natural Computation ambit, Artificial Adaptive Systems are theories which generative algebras are able to create artificial models simulating natural phenomenon. The learning and growing process of the models is isomorphic to the natural process evolution, that is, it's itself an artificial model comparable with the origin of the natural process. We are dealing with theories adopting the "time of development" of the model as a formal model of "time of process" itself. Artificial Adaptive Systems comprise Evolutive Systems and Learning Systems. Artificial Neural Networks are the more diffused and best-known Learning Systems models in Natural Computation. For this reason we present in this paper an application of new Artificial Adaptive Systems to a very hard and pragmatic topic: drug trafficking. That because we think that "real world" is often the best theory.

In order to resolve the key problem of preference representation and utility calculation of negotiator in negotiation support system, preference representation and utility calculation in negotiation support system based on preference representation of psychology is proposed. Firstly model of psychology based on cloud model is proposed. The fuzzy and randomicity is depicted fully in the model. The calculation of preference and utility based on model of artificial psychology based on cloud model is given. The suggested resolution of negotiation is given based on model of artificial psychology based on cloud model by the means of media.

Emotion plays an important role in human life, especially in affective human-computer interaction. Affective computing and artificial psychology are new research fields that involve computer and emotions, they have the same key research aspect, affective modeling. To improve the existing affective models, this article constructs a novel intensity-based affective model that incorporates personality and some psychological factors. To simulate the transitional process of emotions better, some important psychological factors are considered in this affective model, such as activation threshold, emotion elicitors, emotion decay, emotion interactions and so on. Moreover, on the basis of the model, an emotional prediction system is designed and implemented. After volunteers' tests, the system got good effect.

Artificial intelligence and physics are two components of 3D games. While they bring the laws of nature and more realism to games, they may be intensive enough to leave a sizable dent on the game 's performance and lead to a serious reduction in fame rate. In this paper, we discuss a game implementation solution with multi-core architectures which hides the computational load of the game intelligence and improves the gaming experience.

The researches on supply chain are mainly about the conjunction mechanism and efficiency in Integrated supply chain to enhance its competitiveness and the cooperation between its members. But most of those belong to the standard finance field, and few about the factors of human psychology. We studied the satisfaction degree models of customer with mental account based on the customer satisfaction degree (CSD) model and found they are simplified, not reasonable and inaccurate. This paper presents a CSD model based on artificial psychology, which quantify exact customer psychology using cognition and artificial psychology methods, and describes an optimization model of the ISC bi-level distribution network based on artificial psychology.

Nowadays customer preference has aroused concerns in customer satisfaction researches of e-learning, but specifications of user psychology can not been stated clearly in existing tools. This paper describes an individual-centered e-learning tool taking into account the full spectrum of Web mining techniques and activities, presents a multi-agents architecture based on artificial psychology techniques, which will make the e-learning process both adaptable and dynamic, and hence up-to-date. Knowledge base techniques are used to support the adaptation of agents' cycle, and artificial psychology techniques and beliefs techniques are combined to manage preference and experimental knowledge and to realize more effective and more precise knowledge management.