The advent of fuzzy logic controllers has inspired the allocation of new resources for the possible realization of more efficient methods of control. In comparison with traditional controller design methods requiring mathematical models of the plants, one key advantage of fuzzy controller design lies in its model-free approach. Conventionally, the selection of fuzzy if-then rules often relies h...

In many robotics applications, applying reinforcement learning (RL) can be especially difficult, as it depends on the prespecification of a reward function over the environment’s states, which is often hard to define. Inverse Reinforcement Learning (IRL) [1] attempts to address this problem, by utilizing human demonstrations to learn the reward function, without having a human explicitly define...

We present a new reinforcement learning system more suitable to be used in robotics than existing ones. Existing reinforcement learning algorithms are not speci cally tailored for robotics and so they do not take advantage of the robotic perception characteristics as well as of the expected complexity of task that robots are likely to face. In a robot, the information about the environment come...

Reinforcement learning, belief learning, experiments, probability matching, market price-choice games, computer simulations. This paper explains how simple psychological models of reinforcement and belief learning can be used to explain dynamic patterns of adjustment in economics experiments.

The reinforcement learning problem is a very difficult problem when considering real-size applications. To solve it, we think that many issues should be studied altogether. To achieve such an endeavor, we also think that it is quite common that human begins can provide help on-the-fly to the reinforcement learner, that is when he/she sees how the learner is (mis)behaving, or could perform bette...

the main issues in any society are teaching and learning and main elements of this story are the teacher and the learner. there are different psychology schools in which any of them in turn, have taken many extensive researches about behavior, and facts and theories of learning have been studied from a particular perspective. rationalism asserts that the human intellect has the highest energy a...

As a genetics-based machine learning technique, zeroth-level classifier system (ZCS) is based on a discounted reward reinforcement learning algorithm, bucket-brigade algorithm, which optimizes the discounted total reward received by an agent but is not suitable for all multi-step problems, especially large-size ones. There are some undiscounted reinforcement learning methods available, such as ...

There are many interesting topics in artificial intelligence that would be useful to stimulate student interest at various levels of the computer science curriculum. They can also be used to illustrate some basic concepts of computer science, such as arrays. One such topic is reinforcement learning – teaching a computer program how to play a game or traverse an environment using a system of rew...

Although behaviour-based robotics has been successfully used to develop autonomous mobile robots up to a certain point, further progress may require the integration of a learning model into the behaviour-based framework. Reinforcement learning is a natural candidate for this because it seems well suited to the problems faced by autonomous agents. However, previous attempts to use reinforcement ...