FML-based Prediction Agent and Its Application to Game of Go
In this paper, we present a robotic prediction agent including a darkforest Go engine, a fuzzy markup language (FML) assessment engine, an FML-based decision support engine, and a robot engine for game of Go application. The knowledge base and rule base of FML assessment engine are constructed by referring the information from the darkforest Go engine located in NUTN and OPU, for example, the number of MCTS simulations and winning rate prediction. The proposed robotic prediction agent first retrieves the database of Go competition website, and then the FML assessment engine infers the winning possibility based on the information generated by darkforest Go engine. The FML-based decision support engine computes the winning possibility based on the partial game situation inferred by FML assessment engine. Finally, the robot engine combines with the human-friendly robot partner PALRO, produced by Fujisoft incorporated, to report the game situation to human Go players. Experimental results show that the FML-based prediction agent can work effectively.
Code (0)
등록된 구현이 없습니다.
Tasks
Game of GoPredictionSimilar Papers 제목 키워드 기반
Hidden in Plain Text: Measuring LLM Deception Quality Against Human Baselines Using Social Deduction Games
Large Language Model (LLM) agents are increasingly used in many applications, raising concerns about their safety. While previous work has shown that LLMs can deceive in controlled tasks, less is known about their abilit…
Human Choice Prediction in Language-based Persuasion Games: Simulation-based Off-Policy Evaluation
Recent advances in Large Language Models (LLMs) have spurred interest in designing LLM-based agents for tasks that involve interaction with human and artificial agents. This paper addresses a key aspect in the design of …
Decision MakingOff-policy evaluationTrajectory Entropy: Modeling Game State Stability from Multimodality Trajectory Prediction
Complex interactions among agents present a significant challenge for autonomous driving in real-world scenarios. Recently, a promising approach has emerged, which formulates the interactions of agents as a level-k game …
Autonomous DrivingTrajectory PredictionPFML-based Semantic BCI Agent for Game of Go Learning and Prediction
This paper presents a semantic brain computer interface (BCI) agent with particle swarm optimization (PSO) based on a Fuzzy Markup Language (FML) for Go learning and prediction applications. Additionally, we also establi…
Brain Computer InterfaceGame of GoStability Certificates for Receding Horizon Games
Game-theoretic MPC (or Receding Horizon Games) is an emerging control methodology for multi-agent systems that generates control actions by solving a dynamic game with coupling constraints in a receding-horizon fashion. …
Autonomous DrivingDecision Makingvalid