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Full-Text Articles in Engineering
An Efficient Multiple-Place Foraging Algorithm For Scalable Robot Swarms, Qi Lu
An Efficient Multiple-Place Foraging Algorithm For Scalable Robot Swarms, Qi Lu
Computer Science ETDs
Searching and collecting multiple resources from large unmapped environments is an important challenge. It is particularly difficult given limited time, a large search area and incomplete data about the environment. This search task is an abstraction of many real-world applications such as search and rescue, hazardous material clean-up, and space exploration. The collective foraging behavior of robot swarms is an effective approach for this task. In our work, individual robots have limited sensing and communication range (like ants), but they are organized and work together to complete foraging tasks collectively. An efficient foraging algorithm coordinates robots to search and collect …
Amplifying The Collective Intelligence Of Teams With Swarm Ai, David Askay, Lynn E. Metcalf, Louis B. Rosenberg, Gregg Willcox, David Baltaxe
Amplifying The Collective Intelligence Of Teams With Swarm Ai, David Askay, Lynn E. Metcalf, Louis B. Rosenberg, Gregg Willcox, David Baltaxe
Industrial Technology and Packaging
Group decision-making is strengthened by the varied knowledge and perspectives that each member brings, yet teams often fail to capitalize on their diversity. This paper describes how Swarm AI, a novel collaborative intelligence technology modeled on the decision-making process of honey bee swarms, enables networked human groups to more effectively leverage their combined insights. Through an empirical study conducted on 60 small teams, each of 3 to 6 members, we demonstrate the capacity of Swarm AI to significantly amplify the collective intelligence of human groups. A well-known testing instrument—the Reading the Mind in the Eyes (RME) test —was used to …
Enhancing Group Social Perceptiveness Through A Swarm-Based Decision-Making Platform, David A. Askay, Lynn E. Metcalf, Louis Rosenberg, Gregg Willcox
Enhancing Group Social Perceptiveness Through A Swarm-Based Decision-Making Platform, David A. Askay, Lynn E. Metcalf, Louis Rosenberg, Gregg Willcox
Industrial Technology and Packaging
Swarm Intelligence is natural phenomenon that enables social animals to make group decisions in real-time systems. This process has been deeply studied in fish schools, bird flocks, and bee swarms, where collective intelligence has been observed to emerge. The present paper describes swarm.ai—a collaborative technology that enables swarms of humans to collectively converge upon a decision as a real-time system. Then we present the results of a study investigating if groups working as “human swarms” can amplify their social perceptiveness, a key predictor of collective intelligence. Results showed that groups reduced their social perceptiveness errors by more than half when …
Measuring Group Personality With Swarm Ai, Gregg Willcox, David Askay, Louis Rosenberg, Lynn Metcalf, Bryan Kwong, Richard Liu
Measuring Group Personality With Swarm Ai, Gregg Willcox, David Askay, Louis Rosenberg, Lynn Metcalf, Bryan Kwong, Richard Liu
Industrial Technology and Packaging
The aggregation of individual personality tests to predict team performance is widely accepted in management theory but has significant limitations: the isolated nature of individual personality surveys fails to capture much of the team dynamics that drive real-world team performance. Artificial Swarm Intelligence (ASI), a technology that enables networked teams to think together in real-time and answer questions as a unified system, promises a solution to these limitations by enabling teams to take personality tests together and converge upon answers that best represent the group’s disposition. In the present study, the group personality of 94 small teams was assessed by …