Intelligent Agents: Characteristics and Applications
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Compares model-based and model-free reinforcement learning, highlighting the advantages of the former in adapting to reward changes and planning future actions.
Explores socially-aware AI for last-mile mobility, focusing on understanding social etiquettes, anticipating behaviors, and forecasting crowd movements.
Covers planning with adversaries, heuristic search algorithms, and strategies for games with chance, emphasizing the significance of deliberative agents.
Explores how AI/ML is shaping the future workplace, focusing on enterprise systems and processes, and discusses the current state of AI/ML adoption in enterprises.
Explores the challenges and distinctions between human and artificial autonomy, touching on ethical implications and the conditions required for true autonomy.
Explores fundamental principles in scientific research, the impact of computers, numerical algorithms, and deep learning in solving high-dimensional problems.
By Professor David Bresch explores the origins and applications of natural catastrophe modeling, focusing on storms and their impact on risk mitigation and decision-making processes.
