Intelligent and autonomous agents is a subarea of symbolic artificial intelligence where
these agents decide, either reactively or proactively, upon a course of action by reasoning …

Simulations provide a useful methodological approach for studying the behavior of complex
socio-technical information systems (IS), in which humans and IT artifacts interact to process …

We introduce a model for agent-environment systems where the agents are implemented via
feed-forward ReLU neural networks and the environment is non-deterministic. We study the …

There has been considerable progress in both the theory and practice of agent
programming since Georgeff and Rao's seminal work on the belief-desire-intention …

We develop the theoretical foundations of a predicate abstraction methodology for the
verification of multi-agent systems. We put forward a specification language based on …

Abstract The Belief-Desire-Intention (BDI) architecture is a popular framework for rational
agents; existing verification approaches either directly encode simplified (eg lacking features …

For many multiagent control problems, neural networks (NNs) have enabled promising new
capabilities. However, many of these systems lack formal guarantees (eg, collision …

Web search engines are known to cache the results of previously issued queries. The stored
results typically contain the document summaries and some data that is used to construct the …

Intelligent and autonomous agents is a subarea of symbolic artificial intelligence where
these agents decide, either reactively or proactively, upon a course of action by reasoning …

A key advantage of BDI-based agent programming is that agents can deliberate about which
course of action to adopt to achieve a goal or respond to an event. However, while state-of …