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In recent years intelligent agents have been the focus of much attention from the Artificial Intelligence (AI) and many other communities. In AI research, agent-based systems technology has emerged as a new paradigm for conceptualizing, designing, and implementing sophisticated software systems. Furthermore, there has been a move of these systems into safety-critical domains including healthcare, emergency scenarios, and disaster recovery. While agents provide great benefits in developing many complex software applications (e.g., systems that have multiple components, distributed over networks, exhibit dynamic changes, and require autonomous behavior), they also present new challenges to application developers, namely verifying requirements and ensuring functional correctness. These problems become even more challenging in the case of multi- agent systems (MASs), where agents exchange information via messages. Systematic, formal approaches to their specification and verification can allow addressing these problems. The concept of agents, in the setting of this article is used to refer to autonomous reasoning agents, where agents are capable of reasoning about their behavior and interactions. A crucial problem in developing (formal) logical frameworks that model desired agents is to capture the fact that real agents possess limited computational (time and space) and communication resources. In other words, when agents try to achieve goals, each agent in the system requires some basic resources such as time (number of computational steps), space (amount of memory) and perhaps communication bandwidth (number of messages that need to be exchanged)(Formal Approaches to Modelling and Verifying Resource-bounded Agents-state of the Art and Future Prospects, Abdur Rakib)
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Last date updated on September, 2020