Multi-player Cooperative Game Research Articles

Data collection of multi-player cooperative game based on edge computing in mobile crowd sensing

As the number and type of mobile crowd sensing (MCS) data collection increases, more and more computation and processing are required, resulting in higher service cost and service delay, posing a huge challenge to traditional MCS. Currently, edge computing is being introduced to MCS to collect data to reduce service cost and service latency. In the offline mode, there are two issues that need to be addressed with the edge computing-based MCS data collection. First, for large-scale, multi-player, and multiple types of task data, edge servers are limited in computational resources and need to address issues such as task offloading and service cache scheduling. Second, in traditional MCS data collection, workers usually carry in a single type of task data, but it has now been proposed that workers need to carry multiple types of task data. To address the above problems, this paper proposes a joint optimization strategy for edge computing based on multi-player cooperative game and greedy differential evolution algorithm (MCG-GDE) to improve the service rate of edge servers and minimize the service cost and service latency in the data collection. We build a mathematical optimization problem for edge computing based on MCS data collection. The formulation of the optimization problem proves to be a NP-hard problem, so this optimization strategy constructs a task propagation scheme for multi-player cooperative games (MCG), where tasks carried by workers are reassigned to effectively reduce problem complexity and produce sub-optimal solutions to the mathematical model. Then, on the basis of the suboptimal solution, the optimal solution of the problem is obtained by the greedy differential evolution algorithm (GDE). Simulation results demonstrate that MCG-GDE outperforms other baseline strategies.

Cooperative and Competitive Serious Game for Operations and Supply Chain Management

In the last decades, Serious Games (SGs) have been implemented more and more in the engineering field, for both educational and professional purposes. The interest in digital SGs has increased even more in the last years of covid-19 pandemic, due to their location-independent availability and to the possibility to use SGs to apply theoretical knowledge and involve the users in a challenging way. Since the beginning of project XXXX in October 2018, the University of Xxxx started to develop a brand-new SG with a strong focus on Operation and Supply Chain Management. The game has been studied as a multiplayer cooperative and competitive game which projects learners in a fictitious universe where multiple companies compete against each other in the same market. The realization of the game started from the definition of the didactical concept, underwent the user acceptance testing phases (alpha and beta tests) up until reach the release and the corresponding final evaluation feedback.

Initial Design and Testing of Multiplayer Cooperative Game to Support Physical Activity in Schools

Recent studies have shown that children are not adequately physically active and there is a need to increase children’s physical activity. This study describes new opportunities and solutions for using existing games and gamification to increase physical activity among children in Sweden. We adopted the principles of Tic-Tac-Training to redesign, build, and test a classical multiplayer cooperative game, Battleship, to create a PA game that children experience as fun and engaging. The low fidelity prototype of the game was developed using an iterative game development life cycle and tested with 13 young male children aged 8–11 in a real-world informal setting. A mixed-method research approach was used to understand the users’ experiences and the impact of the Battleship-PA game on behavior change regarding physical activity. Research data were collected through audio recordings of interactions, direct observation, and a user experience questionnaire. The results of this study indicate both positive and negative feedback that can be used to improve the game and user experiences. The results from the unfiltered recordings revealed that both teams were competitive, cooperated within their team, and became excited whenever they destroyed opponent’s ships or were close to winning. However, the children felt bored and exhausted when many gamification tasks were repeated several times in a game session. Direct observation indicated that the children enjoyed the physical activities resulting from playing the game. However, participants who had not previously played the classical version of Battleship were confused about the objectives and concept of the game. The analysis of the user experience questionnaire indicated that most children found the game easy to play, motivating, engaging, interactive, fun, cooperative, competitive, and visually appealing. Furthermore, most children agreed that the game helped them to be physically active and strongly agreed that they enjoyed performing the physical activities in the game. Future work is needed to improve the game user interface, gamification elements, and prepare additional physical activity tasks for a rewarding experience.

Optimisation of group batch scheduling in flexible flow shop based on multi-player cooperative game

Optimisation of group batch scheduling in flexible flow shop based on multi-player cooperative game

Optimisation of group batch scheduling in flexible flow shop based on multi-player cooperative game

In a flexible flow shop, if there are group batch processes, the processing task needs to form multiple batches for production in the batch operation. In order to make up batch processing, there will be job-waiting time thereby extending the total working hours of the production process, and the conflict between various production indexes is further intensified. Therefore, this paper first establishes the group batch scheduling of flexible flow shop (GBSFFS) mathematical model, and proposes a local scheduling method based on multi-player cooperation and complete information static game, establishes a method of game elements such as game information, game player, game strategy, game payoff for group batch processing, and uses the method for behaviour prediction of various game players, that is, the valuation indexes, which reduce the evaluation indexes conflict in the GBSFFS problem. On the premise of reducing the waiting time, other evaluation indexes have been increased.

Research on Conflict Resolution Method of Production Evaluation Index in Flexible Manufacturing Field Based on Multiplayer Cooperative Game

Multiple local assignment rules are common in production lines with complex production elements to direct the production process. Different local assignment rules have different degrees of impact on each production evaluation index, which aggravates the conflict between each production evaluation index. In order to solve the problem of increasing conflict among multiple production evaluation indexes in complex production scheduling process, based on the mathematical model of flexible flow shop with limited buffer and public buffer (FFSP-PB), game elements such as game player, game strategy and game order are established according to the idea of multiplayer cooperative game, and design the corresponding game strategy selection method to predict and control the game behavior of each player in the problem. Then a conflict resolution method of production evaluation index based on multiplayer cooperative game is proposed to solve the conflict between multiple production evaluation indexes, and then improve each production evaluation index. Finally, according to the actual production data of a bus manufacturing enterprise based on flexible manufacturing mode, several simulation schemes are designed to analyze and verify the effectiveness and practicability of the proposed method in resolving the conflicts between production evaluation indexes, and provides a reliable new solution for the conflict resolution of production evaluation index in the field of flexible manufacturing.

Behavioral Evaluation of Hanabi Rainbow DQN Agents and Rule-Based Agents

Hanabi is a multiplayer cooperative card game, where only your partners know your cards. All players succeed or fail together. This makes the game an excellent testbed for studying collaboration. Recently, it has been shown that deep neural networks can be trained through self-play to play the game very well. However, such agents generally do not play well with others. In this paper, we investigate the consequences of training Rainbow DQN agents with human-inspired rule-based agents. We analyze with which agents Rainbow agents learn to play well, and how well playing skill transfers to agents they were not trained with. We also analyze patterns of communication between agents to elucidate how collaboration happens. A key finding is that while most agents only learn to play well with partners seen during training, one particular agent leads the Rainbow algorithm towards a much more general policy. The metrics and hypotheses advanced in this paper can be used for further study of collaborative agents.

All Together Now

A common problem for people with disabilities, particularly those who rely on mobility devices, is learning to navigate a new environment. This is especially troublesome for students who are attending a new university and need to figure out how to get from one place to another. All Together Now is a mobile multi-player cooperative game developed for two purposes. First, the game, developed by two computer scientists and a disability studies scholar, is intended to give disabled students a fun way to learn their way around campus, learn how to report accessibility issues on that campus, and make friends with people who have similar disabilities. Second, the game can be used as a way of fostering awareness and advocacy among students without disabilities, by having them work in teams where one member is someone with a disability that causes them to rely on mobility devices. This article describes the implementation of the game within a disability studies course and the results of two pilot tests, with both disabled and non-disabled participants.

Control of Unmanned Underwater Vehicle as a Member of Vehicles Team Performing a Given Task

The article presents the control system of a single underwater vehicle which is a member of the underwater vehicles team. The application of the multi-agent system concept for modelling and controlling a team of homogeneous underwater vehicles is discussed. Issues relating to cooperation actions in the team of underwater vehicles are described and solved using the theory of games and vector quality index. The process of negotiations between the vehicles is modelled as a multiplayer cooperative game. Finally, the water region search tasks performed by a team of cooperating underwater vehicles are presented and discussed taking into account possible vehicle failures happening during task realization.

Quality of Video Oriented and Multi-Meeting Based Routing Algorithm for Video Data Offloading

The increasing popularity of video delivery among mobile users makes the problem of explosive traffic growth becoming more and more serious for traditional wireless networks, and video transmission-based on device-to-device communication through mobile opportunistic networks (MONs) is regarded as an ideal way to resolve this issue. However, data transmission in the MONs is mainly through the two ways: data replication and data forwarding. Thus, to achieve high delivery ratio and low delivery delay, data replication is usually excessively exploited, and the large number of redundant replicas will not only consume large amount of nodal resource but also greatly increase the overload of networks. For video transmission, this issue becomes more severe for its volume and continuity. Thus, in this paper, we propose a novel routing scheme for video data transmission in the MONs, namely, video routing-based multi-player cooperative game which can maximize the quality of reconstructed video data while minimizing the overhead of nodal and network resources. Specifically, we first construct the marginal gain model for video delivery quality, and then model the video data transmission among multiple encounters as a multi-player cooperative game. Under the guidance of the Nash equilibrium theory, the video data carried by these encountering nodes is adaptively and optimally re-assigned among them. Extensive simulations based on real-life mobility traces and synthetic traces have validated the effectiveness of the proposed routing algorithm.

MCGR-PB: A Multi-Player Cooperative Game Based Routing for Performance Balancing in Crowd Sensing Networks

Mobile crowd-sensing network is a kind of networks that take advantage of pervasive mobile devices to efficiently collect data and enable the completion of large-scale and complicated sensing tasks through the wide participation of mobile users. Data are delivered based on the opportunistic contacts among mobile uses, and the selection of relay nodes plays a vital role in the performance of such network. In most of existing routing mechanisms, data exchange is still limited between two nodes and they always pursue the maximization of single performance objective, which results in extreme imbalance of performance. Unfortunately, this issue has not yet aroused the full attention of researchers by now. In this paper, to deal with this issue, we estimate the network performance metrics such as delivery success ratio and delivery delay according to the movement model. Aiming at the multi-node meeting scene that often appears in real life, the action of selecting relay nodes is modeled as a multi-player cooperative game with the game goal of maximal performance balancing, and an MCGR-PB was proposed, which can redistribute the packets among the contacting nodes based on Nash equilibrium solution to achieve higher performance balancing. Extensive simulations based on a real-life mobility trace and a synthetic trace have been done, and the results show that compared with other protocols, MCGR-PB can greatly balance the overall performance while ensuring the desired delivery performance of the network.

A Novel Approach for Efficient Usage of Intrusion Detection System in Mobile Ad Hoc Networks

Mobile ad hoc networks (MANETs) are self-configuring infrastructureless dynamic wireless networks in which the nodes are resource constrained. Intrusion detection systems (IDSs) are used in MANETs to monitor activities to detect any intrusion in the otherwise vulnerable network. In this paper, we present efficient schemes for analyzing and optimizing the time duration for which the IDSs need to remain active in a MANET. A probabilistic model is proposed, which makes use of cooperation between IDSs among neighborhood nodes to reduce their individual active time. Typically, an IDS has to run all the time on every node to oversee network behavior. This can turn out to be a costly overhead for a battery-powered mobile device in terms of power and computational resources. Hence, in this work, our aim is to reduce the duration of active time of the IDSs without compromising their effectiveness. To validate our proposed approach, we model the interactions between IDSs as a multiplayer cooperative game in which the players have partially cooperative and partially conflicting goals. We theoretically analyze this game and support it with simulation results.

How to Make the Perfect Fireworks Display: Two Strategies for Hanabi

SummaryThe game of Hanabi is a multiplayer cooperative card game that has many similarities to a mathematical “hat guessing game.” In Hanabi, a player does not see the cards in her own hand and must rely on the actions of the other players to determine information about her cards. This article presents two strategies for Hanabi. These strategies use different encoding schemes, based on ideas from network coding, to efficiently relay information. The first strategy allows players to effectively recommend moves for other players, and the second strategy allows players to determine the contents of their hands. Results from computer simulations demonstrate that both strategies perform well. In particular, the second strategy achieves a perfect score more than 75 percent of the time.

Controlling a team of unmanned underwater vehicles performing water region search tasks

Abstract The article discusses a problem of performing a mission and controlling a team of unmanned underwater vehicles which perform a task of water region search. The team of underwater vehicles has been modelled as a multi-agent system, which made it possible to use the mechanism of multi-agent systems for controlling the team of cooperating underwater vehicles, with each vehicle being treated as an individual agent. Solutions to cooperation problems in multi-agent systems were proposed, including the presentation of the system structure and the data exchange method. Issues relating to cooperation actions in the team of underwater vehicles were described and solved using the theory of games and the vector quality index. The process of negotiations between the vehicles was modelled as the multiplayer cooperative game, which secured successful realisation of the task performed by the team of vehicles with respect to time, which represents the economic aspect of the task. The optimal solution was selected based on the vector quality index, which provided opportunities for minimisation of costs having the form of energy used by the entire team, and maximisation of profits in the form of time needed for completing the water region search task. The proposed method for dividing the action space in the water region search tasks performed by the team of underwater vehicles consists in assigning to each of cooperating underwater vehicles a task the realisation of which contributes to the realisation of the globally defined task. Finally, the results of water region search tasks performed by a team of cooperating underwater vehicles are presented and discussed taking into account possible vehicle failures happening during task realisation.