Agent training techniques study methods to embed empirical, inductive knowledge representations into intelligent agents, in dynamic, recursive or semi-automated ways, expressed in...
Choosing the right representation for a problem is important. In this article we introduce a linear genetic programming approach for motif discovery in protein families, and we al...
FLUX is a declarative, CLP-based programming method for the design of agents that reason logically about their actions and sensor information in the presence of incomplete knowledg...
The paper presents DLV+ a Disjunctive Logic Programming system with object-oriented constructs, including classes, objects, (multiple) inheritance, and types. DLV+ is built on top ...
Francesco Ricca, Nicola Leone, Valerio De Bonis, T...
Alternating-time Temporal Logic (ATL) [1] is used to reason about strategic abilities of agents. Aiming at strategies that can realistically be implemented in software, many varia...