The least-squares policy iteration approach works efficiently in value function approximation, given appropriate basis functions. Because of its smoothness, the Gaussian kernel is a popular and useful choice as a basis function. However, it does not allow for discontinuity which typically arises in real-world reinforcement learning tasks. In this paper, we propose a new basis function based on ...

In this paper, we present the implementation, both in a simulator and in a real-robot version, of an efficient solution to the so-called dynamical nightwatch’s problem on the micro-robot Khepera. The problem consists mainly in exploring a previously unknown environment while detecting, registering and recognizing light sources which may dynamically be turned on and off. At the end of each round...

Reinforcement learning (RL) offers a set of various algorithms for in-situation behavior synthesis [1]. The Qlearning [2] technique is certainly the most used of the RL methods. Multilayer perceptron implementations of the Q-learning have been proposed early [3], due to the interest of the restricted memory need and the generalization capability [4]. Self-organizing map implementation of the Q-...

In recent years, a great deal of interest has been focused on the control of mobile multi-robot systems. The primary reason for this interest in mobile multi-robot systems within the robotics research community is that such systems hold several advantages over single-robot systems. For example, these systems have the capability to quickly explore a large area, and for transporting heavy objects...

Reliable and efficient material transport is one of the basic requirements that affect productivity in industry. For that reason, in this paper two approaches are proposed for the task of intelligent material transport by using a mobile robot. The first approach is based on applying genetic algorithms for optimizing process plans. Optimized process plans are passed to the genetic algorithm for ...

A key issue in the research of an autonomous mobile robot is the design and development of a navigation technique that enables the robot to navigate in a real world environment. This paper is focused on the (a) Establishment of a methodology to model the control system that optimizes the behavior rules using Fuzzy Associative Memory (FAM) for mobile robot navigation. The existing methods focuse...

Locusts possess a bilateral pair of uniquely identifiable visual neurons that respond vigorously to the image of an approaching object. These neurons are called the lobula giant movement detectors (LGMDs). The locust LGMDs have been extensively studied and this has lead to the development of an LGMD model for use as an artificial collision detector in robotic applications. To date, robots have ...

Is it more e cient to use one or several robots? Will the performance of a group of robots working in a collaborative task be enhanced if the robots can communicate with one another? What learning abilities should the robot(s) be provided with for adapting to a continuously changing environment? We address these three issues in a speci c task, namely learning the topography of an environment wh...

In this paper, we aim to design decision-making mechanisms for a simulated Khepera robot equipped with simple sensors, which integrates over time its perceptual experience in order to initiate a simple signalling response. Contrary to other previous similar studies, in this work the decision-making is uniquely controlled by the time-dependent structures of the agent controller, which in turn ar...