Artificial Intelligence and Multi-Agent Systems

Aims:

The Artificial Intelligence and Multi-Agent Systems Section is dedicated to the core algorithms, theories, and formalisms that constitute the field of AI. This Section aims to publish fundamental research on creating agents that can perceive their environment and take actions to achieve specific goals. It covers a broad spectrum from symbolic AI and knowledge-based systems to modern probabilistic and bio-inspired algorithms. The focus is on the theoretical underpinnings, algorithmic innovations, and the application of these core AI techniques to solve complex, structured problems across various domains.

Scope:

This Section covers the fundamental theories and algorithms of AI. Key topics include the following:

• Artificial Intelligence Algorithms: Search, optimization, planning, scheduling, knowledge representation, and reasoning.
• Cognitive Theory and AI: Bridging human cognitive processes with algorithmic design.
• Robots and Autonomous Control Systems: AI for perception, path planning, and control in physical systems.
• Application of AI in Control Systems, Bioinformatics, and Smart Grids.
• Expert Systems and Knowledge-Based Systems.
• AI for Game Theory and Strategic Decision Making.