Ontologies are a powerfull alternative to reinforcement learning. They store knowledge in a domain-specific language. The best-practice for implementing ontologies is a distributed version control system which is filled manually by programmers.

We present an ART-based neural network model (adapted from [2]) of the development of discrimination-shift learning that models the trial-by-trial learning process in great detail. In agreement with the results of human participants (4–20 years of age) in [1] the model revealed two distinct learning modes in the learning process: (1) a discontinuous rational learning process by means of hypothe...

In many multi-agent applications such as distributed sensor nets, a network of agents act collaboratively under uncertainty and local interactions. Networked Distributed POMDP (ND-POMDP) provides a framework to model such cooperative multi-agent decision making. Existing work on ND-POMDPs has focused on offline techniques that require accurate models, which are usually costly to obtain in pract...

In many multi-agent applications such as distributed sensor nets, a network of agents act collaboratively under uncertainty and local interactions. Networked Distributed POMDP (ND-POMDP) provides a framework to model such cooperative multi-agent decision making. Existing work on ND-POMDPs has focused on offline techniques that require accurate models, which are usually costly to obtain in pract...

Designing distributed controllers for self-reconfiguring modular robots has been consistently challenging. We have developed a reinforcement learning approach which can be used both to automate controller design and to adapt robot behavior on-line. In this paper, we report on our study of reinforcement learning in the domain of self-reconfigurable modular robots: the underlying assumptions, the...

The penetration of unmanned aerial vehicles (UAVs) is an essential and important link in modern warfare. Enhancing UAV’s ability autonomous through machine learning has become a research hotspot. However, the current generation strategies for UAVs faces problem excessive sample demand. To reduce demand, this paper proposes combination policy (CPL) algorithm that combines distributed reinforceme...