Game and decision theories have proved to be powerful tools with which to design autonomous agents, and to understand interactions in systems composed of many such agents.
Decision theory provides a general paradigm for designing agents that can operate in complex uncertain environments, and can act rationally to maximize their preferences. Decision-theoretic models use precise mathematical formalism to define the properties of the agent's environment, the agent's sensory capabilities, the ways the agent's actions change the state of the environment, and the agent's goals and preferences. The agent's rationality is defined as behavior that maximizes the expectation of the degree to which the preferences are achieved over time, and the planning problem is identified as a search for the rational, or optimal, plan.
Game theory adds to the decision-theoretic framework the idea of multiple agents interacting within a common environment. It provides ways to specify how agents, separately or jointly, can change the environment and how the resulting changes impact their individual preferences. Building on the assumption that agents are rational and self-interested, game theory uses notions such as Nash equilibrium to design mechanisms and protocols for various forms of interaction and communication that result in the overall system behaving in a stable, efficient, and fair manner.
Descriptions of deployed systems are welcome. We are also interested in the use of non-standard variants of decision theory (including qualitative and logical approaches), and in approaches that combine decision and game theories.
Please submit the paper electronically (at most 15 pages standard LaTeX article style) electronically in postscript (preferred) or pdf, to Piotr Gmytrasiewicz at email@example.com. Authors will be notified about the acceptance of their papers on May 10, and the final camera-ready versions of papers will be due May 20.
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