Recently, 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.
Recent research has sought to merge advances in decision and game theories to build agents that may
operate in complex uncertain environments shared with other agents. This research has investigated
the pitfalls of Nash equilibrium as a solution concept, focused on epistemological advances in game theory
and expressive ways to model agents, and looked into new solution concepts all with the aim of designing
autonomous agents that may robustly interact with other, highly sophisticated agents in both cooperative and
Applications of intelligent agent technologies in multi-agent systems are numerous.
While prototypical agents are physical, like robots, widely useful are also agents that
operate in virtual and electronic environments, like the Internet. They can fetch and filter information,
trade, negotiate and participate in auctions on behalf of their human users, and propose solutions to
transportation, manufacturing and financial allocation problems.
The proposed workshop will provide a unique common platform for researchers and practitioners
of decision theory and game theory to publish novel work, initiate dialog, and get exposed to
the emerging research challenges of designing multi-agent systems. It builds on previous, highly
successful workshops and tutorials with a similar theme that we have organized since the past several years.
Research in the topics of this workshop typically appears scattered across multiple conferences
such as AAMAS, AAAI, TARK and congresses and journals on game theory.
Therefore, to facilitate progress, there is need for a single forum that will collate, compare,
contrast, and disseminate such results. There is much to be gained from bringing together researchers
interested in decision theory and game theory to present recent advances and work on application of
these techniques to multi-agent computing.
The workshop will solicit papers dealing with (but not limited to):
- Theoretical developments in decision theory or game theory applied to interactive settings
- Theoretical developments in interactive epistemology
- Advances in integrating decision theory and game theory
- Advances in modeling strategic agent behavior including humans
- Advances in rational communication among agents
- Descriptions of multi-agent systems employing decision theory or game theory
- Empirical evaluations of multi-agent systems employing decision theory or game theory
- Non-standard variants of decision theory (including qualitative and logical approaches)
applicable to interactions
- Position statements about the use of decision theory or game theory in multi-agent systems
- Descriptions of deployed systems will be also welcome