The Problem of Signal and Symbol Integration: A Study of Cooperative Mobile Autonomous Agent Behaviors

This paper explores and reasons about the interplay between symbolic and continuous representations. We first provide some historical perspective on signal and symbol integration as viewed by the Artificial Intelligence (AI), Robotics and Computer Vision communities. The domain of autonomous robotic agents residing in dynamically changing environments anchors well different aspects of this integration and allows us to look at the problem in its entirety. Models of reasoning, sensing and control actions of such agents determine three different dimensions for discretization of the agent-world behavioral state space. The design and modeling of robotic agents, where these three aspects have to be closely tied together, provide a good experimental platform for addressing the signal-to-symbol transformation problem. We present some experimental results from the domain of cooperating mobile agents involved in tasks of navigation and manipulation

Exception handling in distributed workflow systems using mobile agents

2005-2006 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe

Multi-Agent Coverage Control with Energy Depletion and Repletion

We develop a hybrid system model to describe the behavior of multiple agents cooperatively solving an optimal coverage problem under energy depletion and repletion constraints. The model captures the controlled switching of agents between coverage (when energy is depleted) and battery charging (when energy is replenished) modes. It guarantees the feasibility of the coverage problem by defining a guard function on each agent's battery level to prevent it from dying on its way to a charging station. The charging station plays the role of a centralized scheduler to solve the contention problem of agents competing for the only charging resource in the mission space. The optimal coverage problem is transformed into a parametric optimization problem to determine an optimal recharging policy. This problem is solved through the use of Infinitesimal Perturbation Analysis (IPA), with simulation results showing that a full recharging policy is optimal

Optimal Event-Driven Multi-Agent Persistent Monitoring of a Finite Set of Targets

We consider the problem of controlling the movement of multiple cooperating agents so as to minimize an uncertainty metric associated with a finite number of targets. In a one-dimensional mission space, we adopt an optimal control framework and show that the solution is reduced to a simpler parametric optimization problem: determining a sequence of locations where each agent may dwell for a finite amount of time and then switch direction. This amounts to a hybrid system which we analyze using Infinitesimal Perturbation Analysis (IPA) to obtain a complete on-line solution through an event-driven gradient-based algorithm which is also robust with respect to the uncertainty model used. The resulting controller depends on observing the events required to excite the gradient-based algorithm, which cannot be guaranteed. We solve this problem by proposing a new metric for the objective function which creates a potential field guaranteeing that gradient values are non-zero. This approach is compared to an alternative graph-based task scheduling algorithm for determining an optimal sequence of target visits. Simulation examples are included to demonstrate the proposed methods.Comment: 12 pages full version, IEEE Conference on Decision and Control, 201

An Optimal Control Approach for the Data Harvesting Problem

We propose a new method for trajectory planning to solve the data harvesting problem. In a two-dimensional mission space, $N$ mobile agents are tasked with the collection of data generated at $M$ stationary sources and delivery to a base aiming at minimizing expected delays. An optimal control formulation of this problem provides some initial insights regarding its solution, but it is computationally intractable, especially in the case where the data generating processes are stochastic. We propose an agent trajectory parameterization in terms of general function families which can be subsequently optimized on line through the use of Infinitesimal Perturbation Analysis (IPA). Explicit results are provided for the case of elliptical and Fourier series trajectories and some properties of the solution are identified, including robustness with respect to the data generation processes and scalability in the size of an event set characterizing the underlying hybrid dynamic system

Frad-hoc: a framework to routing ad-hoc networks

This article presents a routing framework for mobile ad-hoc networks, which was called as FRAd-hoc. The main goal of the contribution was the design and implementation of a structure that could gather generic characteristics from hybrid routing algorithm domains.Therefore, it is possible to offer a specializing framework to produce and make available reusable software components. The results present in this research work indicate that the FRAd-hoc environment has reached a successful level, because it was possible to produce others algorithms starting from the proposed framework.1st IFIP International Conference on Ad-Hoc NetWorkingRed de Universidades con Carreras en Informática (RedUNCI

Extended Bandwidth Optimized and Energy Efficient Dynamic Source Routing Protocol in Mobile Ad-hoc Networks

With the increase in the evolution of wireless communication, the ad-hoc networks are gaining attention and are significantly becoming the technology solutions to the various problems. Mobile ad-hoc Networks (MANETs) are envisaged to grow as a main component in the today 4G architecture, and ad hoc networks are projected to be a significant element of the whole future wireless communication. The MANETs are infrastructure less, self-forming and self-organizing network in which there is no control of any centralized entity. The nodes are free to move around the network with dynamic topology. But this self formation, flexibility and scalability create many challenges and design constraints like hidden  terminal, limited bandwidth, limited energy of a node, unpredictable change in the topology etc. Bandwidth and energy are the scarce resources of the network. In order to effectively manage the consumption of bandwidth and energy, an algorithm is proposed which is the extension of traditional Dynamic Source Routing (DSR) reactive routing protocol. The extended protocol applies the mobile agents to carry the data. The proposed work is intended to optimize the bandwidth and making the protocol energy efficient