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In this paper, inspired by the society of animals, we study the coalition formation of robots for detecting intrusions using game theory. We consider coalition formation in a group of three robots that detect and capture intrusions in a closed curve loop. In our analytical model, individuals seek alliances if they think that their detect regions are too short to gain an intrusion capturing probability larger than their own. We assume that coalition seeking has an investment cost and that the formation of a coalition determines the outcomes of parities, with the detect length of a coalition simply being the sum of those of separate coalition members. We derive that, for any cost, always detecting alone is an evolutionarily stable strategy (ESS), and that, if the cost is below a threshold, always trying to form a coalition is an ESS (thus a three-way coalition arises).

Although previous bio-inspired models have concentrated on invertebrates (such as ants), mammals such as primates with higher cognitive function are valuable for modeling the increasingly complex problems in engineering. Understanding primates' social and communication systems, and applying what is learned from them to engineering domains is likely to inspire solutions to a number of problems. This paper presents a novel bio-inspired approach to determine group size by researching and simulating primate society. Group size does matter for both primate society and digital entities. It is difficult to determine how to group mobile sensors/robots that patrol in a large area when many factors are considered such as patrol efficiency, wireless interference, coverage, inter/intragroup communications, etc. This paper presents a simulation-based theoretical study on patrolling strategies for robot groups with the comparison of large and small groups through simulations and theoretical results.

Although previous bio-inspired models have concentrated on invertebrates, such as ants, mammals, such as primates with higher cognitive function, are valuable for modeling the increasingly complex problems in engineering. Understanding primates' social and communication systems and applying what is learned from them to engineering domains will likely lead to solutions to a number of problems. Scent-marking is an important behavior among primates and many other mammals. In this article, inspired by primates' scent-marking activity, we propose and study a collaboration strategy for mobile and static sensors with RFID tags, where mobile sensors can be treated as robots or mobile actuators and can leave information to direct others to find them. Mobile sensors are equipped with RFID tags (or sensors) that can be deployed whenever needed, and RFID tags (or sensors) carry related information for other robots to pick up. We propose several primate-inspired communication mechanisms, including delayed-and-relayed and scenttrail communication among robots. We analytically model and simulate scent-trail communication. We also study a tracking and pursuing scheme of mobile sensors using simulations in terms of robot speeds, searching function, deployment density, turning function, and so on. We assume that robots (mobile sensors or mobile actuators) are capable of deploying/throwing-out sensors/RFID tags.

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