Multi-Agent Systems require coordination mechanisms in order to assemble the behaviour of autonomous and heterogeneous agents and achieve the desired performance of the whole system. Norms are deontic statements employed by these coordination mechanisms which define constraints to the potential excesses of agents’ autonomous behaviour. However, norms are only effective if agents are capable of ...

We have designed and implemented autonomous software agents. Our agents are programs that can move independently through a heterogeneous network of computers. They can sense the state of the network, monitor software conditions, and interact with other agents. The network-sensing tools allow our agents to adapt to the network configuration and to navigate under the control of reactive plans. In...

We study the resource-bounded autonomous agents acting in complex multi-agent and multi-task environments. In particular, we investigate various models of the agent action selection in such environments. Designing such autonomous decision making agents for non-episodic and partially observable dynamic environments is particularly challenging, due to a high-level demand such environments pose in...

Research on multi-agent systems, in which autonomous agents are able to learn cooperative behavior, has been the subject of rising expectations in recent years. We have aimed at the group behavior generation of the multi-agents who have high levels of autonomous learning ability, like that of human beings, through social interaction between agents to acquire cooperative behavior. The sharing of...

Privacy has been a concern for humans long before the explosive growth of the Internet. The advances in information technologies have further increased these concerns. This is because the increasing power and sophistication of computer applications offers both tremendous opportunities for individuals, but also significant threats to personal privacy. Autonomous agents and Multi-agent Systems ar...

While many learning algorithms as well as dynamic growing and pruning techniques are appropriate for most technical applications, they do not work appropriately in the context of autonomous agents. Autonomous agents potentially operate in dynamically changing environments. They receive an endless data stream, which makes it impossible to store a fixed set of training patterns. Therefore, autono...

 In this paper, we present DTP (Distributed Task Plan), a model to depict distributed tasks for executions by mobile agents. DTP is composed of autonomous primitives and can generate the autonomous workflow when a mobile agent executes it. DTP provides mobile agents with navigational and computational autonomies when transporting through the underlying computational network. A mobile agent pla...

As we move towards a richer model of computation based on interactions among autonomous agents in lieu of the more traditional numeric batch processing model, it is necessary to devise techniques and abstractions for the development of such autonomous agents. The ability to generate, reason about, and select the means to achieve explicit goals is critical for autonomous agents, the so called go...

When agents make decisions, they have to deal with norms regulating the system. In this paper we therefore propose a rule-based qualitative decision and game theory combining ideas from multiagent systems and normative systems. Whereas normative systems are typically modelled as a single authority that imposes obligations and permissions on the agents, our theory is based on a multiagent struct...

As autonomous robots become more complex in their behavior, more sophisticated software architectures are required to support the ever more sophisticated robotics software. These software architectures must support complex behaviors involving adaptation and learning, implemented, in particular, by neural networks. We present in this paper a neural based schema [2] system architecture for the de...