The Independent Choice Logic for modelling multiple agents under uncertainty

David Poole

In Artificial Intelligence, Volume 94, Numbers 1-2, Special Issue on Economic Principles of Multi-agent Systems, pages 5-56, 1997.


Inspired by game theory representations, Bayesian networks, influence diagrams, structured Markov decision process models, logic programming, and work in dynamical systems, the independent choice logic (ICL) is a semantic framework that allows for independent choices (made by various agents including nature) and a logic program that gives the consequence of choices. This representation can be used as a (runnable) specification for agents that act in a world, make observations of that world and have memory, as well as a modelling tool for dynamic environments with uncertainty. The rules specify the consequences of an action, what can be sensed and the utility of outcomes. This paper presents a possible-worlds semantics, and shows how to embed influence diagrams, structured Markov decision processes, and both the strategic (normal) form and the extensive (game-tree) form of a game within the ICL. It's argued that the ICL provides a natural and concise representation for multi-agent decision-making under uncertainty that allows for the representation of structured probability tables, the dynamic construction of networks (through the use of logical variables) and a way to handle uncertainty and decisions in a logical representation.

You canget the pdf or the postscript. There there are also slides (in PDF format) from a talk "The Independent Choice Logic: A pragmatic combination of logic and decision theory", March 1998.

Related Papers

D. Poole, Abducing Through Negation As Failure: Stable models in the Independent Choice LogicJournal of Logic Programming, 1999.

See also ongoing research. You can get the ICL code distribution.

Last updated 18 April 97 - David Poole