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This chapter advocates for a reconciliation of argumentation theory and formal logic in an agent-centered theory of reasoning, that is, a theory in which inferences are studied as human activities. First, arguments in favor of a divorce between the two fields are presented. Those arguments are not so controversial. However, rather than forcing a radical separation, they urge logicians to rethink the object of their studies. Arguments cannot be analyzed as objects independent from human activity, whether it is dealt with deductive or nondeductive reasoning. The present analysis naturally takes place in the context of dialogical logic in which the proof process and the semantics are conceived in terms of argumentative games, which involve the agents, their commitments and their actions. This work focuses first on deductive reasoning and then takes abduction as a case of nondeductive reasoning. By relying on some relevant ideas of the Gabbay–Woods (GW) schema of abduction and Aliseda’s approach, a new dialogical explanation of abduction in terms of concession-problem is proposed. This notion of concession problem will be defined thereafter. With respect to the topics of the model-based sciences, the question of the specificity of the speech act by means of which a hypothesis is conjectured is set more specifically.

The chapter addresses the philosophical issues raised by the use of hypothetical modeling in the social sciences. Hypothetical modeling involves the construction and analysis of simple hypothetical systems to represent complex social phenomena for the purpose of understanding those social phenomena. To highlight its main features hypothetical modeling is compared both to laboratory experimentation and to computer simulation. In analogy with laboratory experiments, hypothetical models can be conceived of as scientific representations that attempt to isolate, theoretically, the working of causal mechanisms or capacities from disturbing factors. However, unlike experiments, hypothetical models need to deal with the epistemic uncertainty due to the inevitable presence of unrealistic assumptions introduced for purposes of analytical tractability. Computer simulations have been claimed to be able to overcome some of the strictures of analytical tractability. Still they differ from hypothetical models in how they derive conclusions and in the kind of understanding they provide. The inevitable presence of unrealistic assumptions makes the legitimacy of the use of hypothetical modeling to learn about the world a particularly pressing problem in the social sciences. A review of the contemporary philosophical debate shows that there is still little agreement on what social scientific models are and what they are for. This suggests that there might not be a single answer to the question of what is the epistemic value of hypothetical models in the social sciences.

The human part of chance-discovery is usually analyzed as an effect of the agent’s knowledge of herself and of her environment. In this paper, setting off from the importance of “understanding the meaning of an impending phenomenon as a chance,” we will analyze how chance-discovery activities are affected and driven by the agent’s ignorance, and the relationship she entertains with the latter. More specifically, we will spell out two kinds of ignorance that are relevant for chancediscovery, also considering which abductive chance-discovery processes they can be related to.