Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Distributed Constraint Optimization (DCOP) is a general framework that can model complex problems in multi-agent systems. Several current algorithms that solve general DCOP instan...
Performance analysis tools are critical for the effective use of large parallel computing resources, but existing tools have failed to address three problems that limit their scal...
This paper reports experiences and outcomes of designing and developing an agent–based, autonomous mission control system for an unmanned aerial vehicle (UAV). Most UAVs are not...
Abstract. Constraints and preferences are ubiquitous in real-life. Moreover, preferences can be of many kinds: qualitative, quantitative, conditional, positive or negative, to name...