Real world multiagent coordination problems are important issues for reinforcement learning techniques. In general, these problems are partially observable and this characteristic ...
Imagine a group of cooperating agents attempting to allocate tasks amongst themselves without knowledge of their own capabilities. Over time, they develop a belief of their own sk...
Recently, industry has begun investigating and moving towards utility computing, where computational resources (processing, memory and I/O) are availably on demand at a market cos...
— This paper proposes to incorporate bootstrap of data, random feature subspace and evolutionary algorithm with negative correlation learning to automatically design accurate and...
This paper addresses decentralized multi-project scheduling under uncertainty. The problem instance we study is the scheduling of airport ground handling services, where aircraft ...