The Distributed Weighing Problem: A Lesson in Cooperation Without Communication

Bosse, Tibor; Hoogendoorn, Mark; Jonker, Catholijn M.

doi:10.1007/11550648_17

Cited by 3 publications

(3 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…3.3.1. Game 1: "Broken Square" Game The broken square game was proposed by Bavela [43] and has been used mainly as a tool to foster communication, collaboration, and cooperation among different people with a common goal [44]. In this game, the students are grouped in teams of five.…”

Section: Application Of Learning Activitiesmentioning

confidence: 99%

See 1 more Smart Citation

Impact of Game-Based Learning on Understanding Lean Construction Principles

et al. 2019

View full text Add to dashboard Cite

Lean philosophy introduces a new approach for maximizing value while minimizing waste, facilitating sustainable practices at the same time. Companies have become aware of these improvements and are demanding students well formed in Lean concepts. However, to meet this demand, universities must adapt their curricula to include courses that use alternative teaching methods to connect to real contexts. This paper seeks to analyze the benefits of lecture- and game-based learning for developing students’ understanding of Lean Construction Principles. A case study is carried out in the “Lean Construction” course of the Master of Planning and Management in Civil Engineering of the Universitat Politècnica de València. A combination of a traditional lecture and three simple games is applied. Descriptive statistics, the Mann–Whitney U-test, and the Wilcoxon test are performed to analyze the impact of each activity on the understanding of each Lean Construction Principle. Results highlight the importance of combining the lecture class with multiple games to effectively impart knowledge about Lean principles and their application in the construction industry. In addition, they emphasize the importance of selecting the game according to the Lean principle to be taught.

show abstract

Section: Application Of Learning Activitiesmentioning

confidence: 99%

“…The learning objective of the "broken square" game (game 1) was to understand the importance of communication and systemic thinking in work processes [44]. To analyze the significant effect (p-value < 0.05) of the "broken square" game on the level of competence achieved for each LCP, the Wilcoxon test was performed.…”

Section: Session 2: "Broken Square" Gamementioning

confidence: 99%

Impact of Game-Based Learning on Understanding Lean Construction Principles

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Bosse et al presented the distributed weighing problem [16]. Here agents are given positions, or roles, a priori.…”

Section: Cooperation Without Communicationsmentioning

confidence: 99%

Genetic Fuzzy Trees and their Application Towards Autonomous Training and Control of a Squadron of Unmanned Combat Aerial Vehicles

et al. 2015

View full text Add to dashboard Cite

This study introduces the technique of Genetic Fuzzy Trees (GFTs) through novel application to an air combat control problem of an autonomous squadron of Unmanned Combat Aerial Vehicles (UCAVs) equipped with next-generation defensive systems. GFTs are a natural evolution to Genetic Fuzzy Systems, in which multiple cascading fuzzy systems are optimized by genetic methods. In this problem a team of UCAV's must traverse through a battle space and counter enemy threats, utilize imperfect systems, cope with uncertainty, and successfully destroy critical targets. Enemy threats take the form of Air Interceptors (AIs), Surface to Air Missile (SAM) sites, and Electronic WARfare (EWAR) stations. Simultaneous training and tuning a multitude of Fuzzy Inference Systems (FISs), with varying degrees of connectivity, is performed through the use of an optimized Genetic Algorithm (GA). The GFT presented in this study, the Learning Enhanced Tactical Handling Algorithm (LETHA), is able to create controllers with the presence of deep learning, resilience to uncertainties, and adaptability to changing scenarios. These resulting deterministic fuzzy controllers are easily understandable by operators, are of very high performance and efficiency, and are consistently capable of completing new and different missions not trained for.

show abstract