Intention recognition for multiple agents

Zhang, Zhang; Zeng, Yanjun; Jiang, Wenhui; Pan, Yinghui; Tang, Jing

doi:10.1016/j.ins.2023.01.066

Cited by 4 publications

(1 citation statement)

References 18 publications

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“…There are few works focused solely on intention. This work [13] recognized intention among multiple agents by analyzing behaviors over time and refining a prescriptive behavioral model. The authors identify common intentions.…”

Section: Related Workmentioning

confidence: 99%

Robotics Perception: Intention Recognition to Determine the Handball Occurrence during a Football or Soccer Match

Hassan,

Karungaru,

Terada

2024

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In football or soccer, a referee controls the game based on the set rules. The decisions made by the referee are final and can’t be appealed. Some of the decisions, especially after a handball event, whether to award a penalty kick or a yellow/red card can greatly affect the final results of a game. It is therefore necessary that the referee does not make an error. The objective is therefore to create a system that can accurately recognize such events and make the correct decision. This study chose handball, an event that occurs in a football game (Not to be confused with the game of Handball). We define a handball event using object detection and robotic perception and decide whether it is intentional or not. Intention recognition is a robotic perception of emotion recognition. To define handball, we trained a model to detect the hand and ball which are primary objects. We then determined the intention using gaze recognition and finally combined the results to recognize a handball event. On our dataset, the results of the hand and the ball object detection were 96% and 100% respectively. With the gaze recognition at 100%, if all objects were recognized, then the intention and handball event recognition were at 100%.

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Section: Related Workmentioning

confidence: 99%

Robotics Perception: Intention Recognition to Determine the Handball Occurrence during a Football or Soccer Match

Hassan,

Karungaru,

Terada

2024

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Human-Agent Team Based on Decision Matrices: Application to Road Traffic Management in Participatory Simulation

Razakatiana,

Kolski,

Mandiau

et al. 2024

Hum-Cent Intell Syst

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The main motivation for this work is the design of context-sensitive systems, involving a human-agent team. More precisely, the participants in the current context, are human beings and software agents, who have to coordinate themselves for the collaborative achievement of a complex task. We propose a model of interaction between these heterogeneous entities (humans, software agents) based on decision matrices inspired from game theory. The case study concerns the traffic management through intersections, involving several groups composed of human operators and software agents (playing the role of assistants), in a participatory simulation. An evaluation of the results obtained is presented in order to show the feasibility of the proposed approach. We show that despite its simplicity, the interaction model is relatively efficient, because it takes into account context characteristics and the potential availability of software agents.

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Swarm intention identification via dynamic distribution probability image

WANG,

et al. 2024

Chinese Journal of Aeronautics

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Intention recognition for multiple agents

Cited by 4 publications

References 18 publications

Robotics Perception: Intention Recognition to Determine the Handball Occurrence during a Football or Soccer Match

Robotics Perception: Intention Recognition to Determine the Handball Occurrence during a Football or Soccer Match

Human-Agent Team Based on Decision Matrices: Application to Road Traffic Management in Participatory Simulation

Swarm intention identification via dynamic distribution probability image

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