Modern complex games and simulations pose many challenges for an intelligent agent, including partial observability, continuous time and effects, hostile opponents, and exogenous ...
Bayesian Reinforcement Learning has generated substantial interest recently, as it provides an elegant solution to the exploration-exploitation trade-off in reinforcement learning...
This paper presents a path planner for Unmanned Air Vehicles (UAVs) based on Evolutionary Algorithms (EA) that can be used in realistic risky scenarios. The path returned by the a...
Abstract. The increasing adoption of MDD (Model Driven Development) techniques favored the use of large models of different types. It turns out that when the modeled system gets la...
The state of the art commercial query optimizers employ cost-based optimization and exploit dynamic programming (DP) to find the optimal query execution plan (QEP) without evalua...