In this paper, we present an application of Artificial Intelligence (AI) to the design and implementation of Airline Reservation System (ARS). We provide a multi autonomous agent based framework. Autonomous agents are intelligent enough and provide autonomy, simplicity of communication, computation, and a well developed semantics. The steps of design and implementation are discussed in depth, i...

The Autonomous Intelligent Knowledgebuilding Exploration (AIKE) system explores how an autonomous mobile robotic agent using sonar sensors and dead reckoning can learn a map of a completely unknown environment. AIKE generates grid-based maps based on the notion of a "place" (i.e., a location separated from other places by a confining gateway such as a door or entryway). Empirical trials show th...

Cooperating autonomous agents are becoming increasingly attractive for systems where problem solving and decision making must be decentralized. So far, work in this area has focused either on theoretical aspects or on implementation of ad-hoc specialized applications, but neither has led to significant result in the industrial field. One reason for this is that little of the work done can be us...

This paper presents the software system architecturr with the dynamic reconfigurability for highly autonomous systems. The proposed architecture is based on multi-agent model, which is suitable for autonomous, open and distributed systems. Since an agent is too sophisticated as the minimal component that we handle, we define a unit as a simple component of an agent. We present the advanced capa...

Research regarding autonomous learning shows that freeplay does not result in optimal learning. Combining scenario-based training with intelligent agent technology offers the possibility to create autonomous training enriched with automated adaptive support delivered by a director agent. We conducted an experiment to investigate whether directing training scenarios improves the quality of train...

To study the interfacial complexity between an agent and its environment such as the adaptive selection aspects of sensory inputs, we propose a new coupling mechanism, called autonomous coupling, where an agent can spontaneously switch on or off its interaction with the environment. An oscillatory neural system with autonomous coupling sums the sensory inputs and initiates action selection via ...

There are a great deal of approaches in artificial intelligence, some of them also coming from biology and neirophysiology. In this paper we are making a review, discussing many of them, and arranging our discussion around the autonomous agent research. We highlight three aspect in our classification: type of abstraction applied for representing agent knowledge, the implementation of hypothesis...

We propose a variation of the TAC SCM supply-chain trading competition, in which human decision-makers compete with fully-autonomous agents. Because of the complexity and time pressures of the competition environment, humans may be assisted by semi-autonomous agents, which could be modifications of existing agents. The research goal is to discover what kinds of decision support will make a huma...

Abstmcl-Reinforcement learning is an adaptive and flexible control method for autonomous system. In our previous works, we had proposed a reinforcement learning algorithm for redundant systems: "Q-learning with dynamic structuring of exploration space based on GA (QDSEGAY, and applied it to multi-agent systems. However previous works of the QDSEGA have been restricted to homogeneous agents. In ...

The article studies navigability of an autonomous agent in a maze where some rooms may be indistinguishable. In a previous work the authors have shown that the properties of navigability in such a setting depend on whether an agent has perfect recall. Navigability by an agent with perfect recall is a transitive relation and without is not transitive. This article introduces a notion of restrict...