Intro
Preface
Organization
Contents
Main Track
An Open MAS/IoT-Based Architecture for Large-Scale V2G/G2V
1 Introduction
2 Background and Related Work
3 System Architecture
4 Agent Interactions
4.1 Implemented Agent Strategies
5 Experimental Evaluation
5.1 Simulating Algorithms and Mechanisms
6 Conclusions and Future Work
References
.26em plus .1em minus .1emInvestigating Effects of Centralized Learning Decentralized Execution on Team Coordination in the Level Based Foraging Environment as a Sequential Social Dilemma
1 Introduction

2 Background
2.1 Multi Agent Reinforcement Learning (MARL)
2.2 Sequential Social Dilemmas
2.3 Centralized Learning Decentralized Execution (CLDE)
3 Related Work
3.1 MARL Coordination in SSDs
3.2 Learning Algorithms
4 LBF as a SSD
5 Experimental Design
6 Results
7 Conclusion
References
Agent Based Digital Twin of Sorting Terminal to Improve Efficiency and Resiliency in Parcel Delivery
1 Introduction
2 Problem Statement
2.1 State of the Art Analysis Techniques
3 Approach
3.1 Agent Based Realization
3.2 Simulation-Led Experimentation Aid

4 Illustrative Case Study
5 Conclusion
References
Fully Distributed Cartesian Genetic Programming
1 Introduction
2 Distributed Cartesian Genetic Programming
3 Results
3.1 Regression
3.2 N-Parity
3.3 Classification
4 Conclusion
References
Data Synchronization in Distributed Simulation of Multi-Agent Systems
1 Introduction
2 Data Synchronization in Distributed MAS Simulations
3 Synchronization Modes
3.1 Read and Write Operations
3.2 Data Synchronization Interface
3.3 Specification of Proposed Modes
3.4 Properties
4 Experiments

4.1 Experimental Settings
4.2 Results
5 Conclusion
References
Co-Learning: Consensus-based Learning for Multi-Agent Systems
1 Introduction
2 Co-Learning Algorithm
2.1 Consensus-based Multi-Agent Systems
2.2 Algorithm Description
3 Validation of Co-Learning Algorithm
3.1 Convergence Analysis
3.2 Network Efficiency
3.3 Effect of Network Size
4 Execution Using SPADE Agents
4.1 Co-Learning in SPADE
4.2 Execution Example
5 Conclusions
References
Multiagent Pickup and Delivery for Capacitated Agents
1 Introduction
2 Related Work

3 Problem Description
4 Method
4.1 TPMT
4.2 TPMC
5 Evaluation
5.1 Case Studies
5.2 Experimental Setup
5.3 Results
6 Conclusion
References
Using Institutional Purposes to Enhance Openness of Multi-Agent Systems
1 Introduction
2 Artificial Institutions and Purposes
3 Implementing a Multi-agent System with and Without the Purpose Model
3.1 Implementation Without Institutions and Purposes
3.2 Implementation with Institutions and Purposes
4 Discussion About both Implementations
5 Conclusions and Future Work
References