This paper investigates the problem of policy learning in multiagent environments using the stochastic game framework, which we briefly overview. We introduce two properties as de...
We present a dynamic programming approach for the solution of first-order Markov decisions processes. This technique uses an MDP whose dynamics is represented in a variant of the ...
Combinatorial auctions provide a valuable mechanism for the allocation of goods in settings where buyer valuations exhibit complex structure with respect to substitutabilityand co...
The majority of existing language generation systems have a pipeline architecture which offers efficient sequential execution of modules, but does not allow decisions about text c...
Role-limiting approaches using explicit theories of problem-solving have been successful for acquiring knowledge from domain experts1 . However most systems using this approach do...
Constraint propagation is the main feature of any constraint solver. This is thus of prime importance to manage constraint propagation as efficiently as possible, justifying the us...
The ability to handle exceptions, to perform iterated belief revision and to integrate information from multiple sources are essential skills for an intelligent agent. These impor...
Salem Benferhat, Souhila Kaci, Daniel Le Berre, Ma...
Successful image reconstruction requires the recognition of a scene and the generation of a clean image of that scene. We propose to use recurrent neural networks for both analysi...
The algorithm presented here, BCC, is an enhancement of the well known Backtrack used to solve constraint satisfaction problems. Though most backtrack improvements rely on propaga...