Back to Search
Start Over
Opponent Modeling with Information Adaptation (OMIA) in Automated Negotiations
- Source :
- Autonomous Agents and Multiagent Systems ISBN: 9783319716817, AAMAS Workshops (Selected Papers)
- Publication Year :
- 2017
- Publisher :
- Springer International Publishing, 2017.
-
Abstract
- Opponent modeling is an important technique in automated negotiations. Many of the existing opponent modeling methods are focusing on predicting the opponent’s private information to improve the agent’s benefits. However, these modeling methods overlook an ability to improve the negotiation outcomes by adapting to different types of private information about the opponent when they are available beforehand. This availability may be provided by some prediction algorithms, or be prior knowledge of the agent. In this paper, we name the above ability as Information Adaptation, and propose a novel Opponent Modeling method with Information Adaptation (OMIA). Specifically, the future concessions of the opponent will firstly be learned based on the opponent’s historical offers. Then, an expected utility calculation function is introduced to adaptively guide the agent’s negotiation strategy by considering the availability and value of the opponent’s private information. The experimental results show that OMIA can adapt to different types of information, helping the agent reach agreements with the opponent and achieve higher utility values comparing to those which lack the information adaptation ability.
- Subjects :
- Computer science
business.industry
media_common.quotation_subject
02 engineering and technology
Adversary
Machine learning
computer.software_genre
ComputingMethodologies_ARTIFICIALINTELLIGENCE
Negotiation
020204 information systems
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Artificial intelligence
Function (engineering)
business
Adaptation (computer science)
computer
Expected utility hypothesis
media_common
Subjects
Details
- ISBN :
- 978-3-319-71681-7
- ISBNs :
- 9783319716817
- Database :
- OpenAIRE
- Journal :
- Autonomous Agents and Multiagent Systems ISBN: 9783319716817, AAMAS Workshops (Selected Papers)
- Accession number :
- edsair.doi...........8d8ba98457fcb026e3db768a2b2eb168