This workshop held at the University of North Carolina was in the series which started with meetings in the University of New Hampshire (April 1980) and the University of Michigan (April 1981). More than one hundred participants congregated in the Carolina Inn in April 1982 to discuss the status of grand unified theories and their connection to experiment. The spring foliage of Chapel Hill provided a beautiful back-drop to this Third Workshop on Grand Unification. As mentioned in the first talk herein, these three workshops have heard of indications, respectively, of neutrino oscillations, proton decay and a magnetic monopole. Since all three experimental reports remain unconfirmed, grand unifiers must wait expectantly and patiently. These proceedings preserve faithfully the ordering of the workshop talks which followed the tradition of alternation between theory and experiment. Only our introduction will segregate them. The experimental presentations mainly concerned proton decay and massive neutrinos. Four U.S. proton decay experiments were reported: the Brookhaven Irvine-Michigan experiment in the Morton Salt Mine at Fairport Harbor, Ohio was described by WILLIAM KROPP, and ROBERT MORSE represented the Harvard-Purdue-Wisconsin group in the Silver King Mine, Utah. The Homestake Mine, South Dakota and Soudan Mine, Minnesota, experiments were reported respectively by RICHARD STEINBERG and DAVID AYRES, the latter providing also a survey of future U.S. experiments."

Decision makers in large scale interconnected network systems require simulation models for decision support. The behaviour of these systems is determined by many actors, situated in a dynamic, multi-actor, multi-objective and multi-level environment. How can such systems be modelled and how can the socio-technical complexity be captured? Agent-based modelling is a proven approach to handle this challenge. This book provides a practical introduction to agent-based modelling of socio-technical systems, based on a methodology that has been developed at TU Delft and which has been deployed in a large number of case studies. The book consists of two parts: the first presents the background, theory and methodology as well as practical guidelines and procedures for building models. In the second part this theory is applied to a number of case studies, where for each model the development steps are presented extensively, preparing the reader for creating own models.

Decision makers in large scale interconnected network systems require simulation models for decision support. The behaviour of these systems is determined by many actors, situated in a dynamic, multi-actor, multi-objective and multi-level environment. How can such systems be modelled and how can the socio-technical complexity be captured? Agent-based modelling is a proven approach to handle this challenge. This book provides a practical introduction to agent-based modelling of socio-technical systems, based on a methodology that has been developed at TU Delft and which has been deployed in a large number of case studies. The book consists of two parts: the first presents the background, theory and methodology as well as practical guidelines and procedures for building models. In the second part this theory is applied to a number of case studies, where for each model the development steps are presented extensively, preparing the reader for creating own models.

This book constitutes the thoroughly refereed post-conference proceedings of the 21st International Workshop on Multi-Agent-Based Simulation, MABS 2021, held in May 2021 as part of AAMAS 2021. The conference was held virtually due to COVID 19 pandemic. The 14 revised full papers included in this volume were carefully selected from 23 submissions. The workshop focused on finding efficient solutions to model complex social systems, in such areas as economics, management, organizational and social sciences in general. In all these areas, agent theories, metaphors, models, analysis, experimental designs, empirical studies, and methodological principles, all converge into simulation as a way of achieving explanations and predictions, exploration and testing of hypotheses, better designs and systems and providing decision-support in a wide range of applications.