Advances in Science, Technology, and Society - Research Europe

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Temporal Di eren e Learning Applied to a High-Performan e Game ...
TD and MC updates are sample updates because they involve looking ahead to a sample successor state (or state?action pair), using the value ...
Supporting Continuous Consistency in Multiplayer Online Games
In this paper we introduce a new algorithm for updating the parameters of a heuris- tic evaluation function, by updating the heuristic towards the values ...
Mean field games via probability manifold I
UML se décompose en plusieurs sous-ensembles : ? Les vues : elles décrivent un système d'un point de vue donné, qui peut être organisationnel,.
Newton schemes for mean field games - Eventos @ CMM
Temporal difference (TD) learning is a foundational algo- rithm for predicting value functions in reinforcement learn- ing (RL) (Sutton, 1988). In practice, ...
Reinforcement Learning - SNU OPEN COURSEWARE
A total dominating set, abbreviated TD-set, of G is a set S of vertices of G such that every vertex is adjacent to a vertex in S. Thus a set S ? V is a TD-set ...
A-PRIORI ESTIMATES FOR STATIONARY MEAN-FIELD GAMES ...
Abstract. We investigate time-dependent mean-field games with superquadratic Hamiltonians and a power dependence on the measure.
Total version of the domination game - ResearchGate
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Temporal Coherence in TD-Learning for Strategic Board Games
Attractor strategies are positional strategies, i.e. they only depend on the current vertex (no memory needed, nor history of the game).
Games Theory Lesson n°2
We present a new algorithm for temporal difference. (TD) learning which works seamlessly on various games with arbitrary number of players. This is achieved by ...
Temporal Difference Learning with Eligibility Traces for the Game ...
Systems that learn to play board games are often trained by self-play on the basis of temporal difference (TD) learning. Successful examples include Tesauro's ...