Representing and reasoning with an agent's preferences is important in many applications of constraints formalisms. Such preferences are often only partially ordered. One clas...
In this paper, we propose a model named Logical Markov Decision Processes with Negation for Relational Reinforcement Learning for applying Reinforcement Learning algorithms on the ...
Open Answer Set Programming (OASP) is an attractive framework for integrating ontologies and rules. In general OASP is undecidable. In previous work we provided a tableau-based alg...
A robot must often react to events in its environment and exceptional conditions by suspendingor abandoning its current plan and selecting a new plan that is an appropriate respons...
Current approaches to compute and exploit the flexibility of a component in an FSM network are all at the symbolic level [23, 30, 33, 31]. Conventionally, exploitation of this ï¬...