Multi agent learning systems pose an interesting set of problems: in large environments agents may develop localised behaviour patterns that are not necessarily optimal; in a pure...
The training of support vector machines (SVM) involves a quadratic programming problem, which is often optimized by a complicated numerical solver. In this paper, we propose a muc...
Obtaining an accurate multiple alignment of protein sequences is a difficult computational problem for which many heuristic techniques sacrifice optimality to achieve reasonable r...
Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...
: An adhoc network is a collection of wireless mobile nodes dynamically forming a temporary network without the use of any existing network infrastructure or centralized administra...