首页|Understanding Human and Machine Interaction from Decision Perspective:An Empirical Study Based on the Game of Go
Understanding Human and Machine Interaction from Decision Perspective:An Empirical Study Based on the Game of Go
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The authors aim to interpret human and AI interactions from the decision perspective.The authors decompose the interaction analysis into the following main components in the context of interactions:Individual behavior patterns,interaction relationships,and comprehensive analysis.The authors interpret intertemporal decisions from a physical perspective and employ cross-discipline concepts and methodologies to extract the behavior characteristics of players in the empirical case study.About the individual behavior patterns,the authors find that human players prefer short-term periods to AI in decision-making.The interaction relationship analysis reveals a dynamic relationship between possible short-term co-movement and nearly counter-movement in the long run.The authors apply principal component analysis to descriptive indicators and discover a regular decision hierarchy.The main behavior pattern of players in the game of Go is switching between careful and daring behaviors.The differences in the decision hierarchies imply a discrepancy of patience between humans and AI.
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