Abstract--In the Relational Reinforcement learning framework, we propose an algorithm that learns an action model allowing to predict the resulting state of each action in any give...
We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. denite clause programs containing probabilistic facts with a ...
In this paper, we present a dynamic logic for a propositional version of the agent programming language 3APL. A 3APL agent has beliefs and a plan. The execution of a plan changes a...
M. Birna van Riemsdijk, Frank S. de Boer, John-Jul...
This article goes to the foundations of Statistical Inference through a review of Carnap's logic theory of induction. From this point of view, it brings another solution to t...
New, simple, proofs of soundness (every representable function lies in a given complexity class) for Elementary Affine Logic, LFPL and Soft Affine Logic are presented. The proofs ...