Abstract. Today's models for propagation-based constraint solvers require propagators as implementations of constraints to be at least contracting and monotonic. These models ...
We use reinforcement learning (RL) to compute strategies for multiagent soccer teams. RL may pro t signi cantly from world models (WMs) estimating state transition probabilities an...
In this paper, we discuss the problem of generating natural anaphora in assembly instructional texts. We rst present a detailed account of grammatical and lexical anaphora and we e...
Upper bound constraints are often set when complex scientific or business processes are modelled as grid workflow specifications. However, many existing processes such as climate ...
This paper presents a novel, unified distributed constraint satisfaction framework based on automated negotiation. The Distributed Constraint Satisfaction Problem (DCSP) is one t...