tailieunhanh - Socially Intel. Agents Creating Rels. with Comp. & Robots - Dautenhahn et al (Eds) Part 14

Tham khảo tài liệu 'socially intel. agents creating rels. with comp. & robots - dautenhahn et al (eds) part 14', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 244 Socially Intelligent Agents The unbounded formulation of such an economical problem has long been the central concern of classic game theory which has produced a number of models of social choice. For this reason game theory models have become strong candidates for models of social agents. Surprisingly such apparently simple games can be used to conceptualize a variety of synthetic meaningful and formal prototypical context as games. Therefore such models can be used to design and engineer multi-agent systems as well as analyze the behaviour of the resulting social artifact using the logical tools of the models. However the underlying unbounded assumptions of classic game theory is problematic for the design of computational systems 2 . Artificial Intelligence AI on the other hand has long considered models of the relationship between knowledge computation and the quality of solution henceforth referred to as the K-C-Q relationship 7 . AI has shown that there exists a hierarchy of tradeoffs between K C and Q with models that achieve perfect optimal results like game theory models but at the cost of requiring omniscience and unbounded agents to models that sacrifice optimality of Q for a more realistic set of requirements over K and C 12 . Different agent architectures are then entailed from different K-C-Q relationship theories. In the next two sections two such computational models of negotiation are proposed one deductive and the other agent-based simulation that can be analyzed as two different games. The aim of these models has been to attempt to address some of the computational and knowledge problems mentioned above. In particular in the first model the types of problems of interest is when K is limited because agents have at best imperfect and at worst no knowledge of the others utility functions. The best an agent can do is to reason with imperfect knowledge by forming approximations of others utilities. In the second model the knowledge problem is even