Games and Simulations: Learning by Playing and Pretending in Virtual Worlds

2011 ◽  
pp. 323-398
Author(s):  
Lea Kuznik

Virtual worlds for adults (e.g. Second Life), youth (e.g. Habbo) and children (e.g. Whyville) have a great potential for learning and teaching practices for enriching wider public and engendering collective experience and collaboration. Informal learning environments such as educational virtual worlds offer children and adults various intellectual and sensory activities or »crystallized« experiences with reinforcing multiple intelligences, according to Gardner. Virtual worlds promote social interaction and offer visitors an opportunity for various interactive activities which can sometimes not be realized in real life education. Children and adults can explore and learn in a different way and from a different perspective, e.g. with educational games and simulations. Virtual worlds represent a new medium that allows people to connect in new virtual ways and offer new challenges in the educational field.


Author(s):  
Scott J. Warren ◽  
Greg Jones ◽  
Beth Dolliver ◽  
Richard A. Stein

In the context of instructional design and educational research, there remains a vexing question. What is a game? How is it different from simulations? In turn, how is each distinct from virtual worlds? A review of the literature on the use of games for learning reveals either a complete lack of definition by authors or some wide disparities in terms of how each explains the necessary components that make up either a game in general, or an educational game specifically. Without clear definitions to which theorists can use to discuss their myriad learning designs, the findings that emerge from research may not translate effectively into useful discourse because there is no agreement as to whether the original design qualifies as a game or simulation. This paper explores the historical evolution of the definitions of the terms in the fields of philosophy and education and suggests a means by which they may be constructed and dynamically updated.


Author(s):  
Iskander Umarov ◽  
Maxim Mozgovoy

The rapid development of complex virtual worlds (most notably, in 3D computer and video games) introduces new challenges for the creation of virtual agents, controlled by Artificial Intelligence (AI) systems. Two important sub-problems in this topic area that need to be addressed are (a) believability and (b) effectiveness of agents' behavior (i.e. human-likeness of the characters and high ability to achieving their own goals). In this chapter, the authors study current approaches to believability and effectiveness of AI behavior in virtual worlds. They examine the concepts of believability and effectiveness and analyze several successful attempts to address these challenges. In conclusion, the authors provide a case study that suggests that believable and effective behavior can be achieved through learning behavioral patterns from observation with subsequent automatic selection of effective acting strategies.


PsycCRITIQUES ◽  
2008 ◽  
Vol 53 (51) ◽  
Author(s):  
Richard Velayo
Keyword(s):  

PsycCRITIQUES ◽  
2010 ◽  
Vol 55 (2) ◽  
Author(s):  
Janet F. Carlson
Keyword(s):  

PsycCRITIQUES ◽  
2012 ◽  
Vol 57 (50) ◽  
Author(s):  
Vincent W. Hevern

2011 ◽  
Author(s):  
Aarti Shyamsunder ◽  
Michael S. Fetzer ◽  
Wendy L. Bedwell ◽  
Ben Hawkes ◽  
Charles A. Handler ◽  
...  
Keyword(s):  

AI Magazine ◽  
2019 ◽  
Vol 40 (3) ◽  
pp. 67-78
Author(s):  
Guy Barash ◽  
Mauricio Castillo-Effen ◽  
Niyati Chhaya ◽  
Peter Clark ◽  
Huáscar Espinoza ◽  
...  

The workshop program of the Association for the Advancement of Artificial Intelligence’s 33rd Conference on Artificial Intelligence (AAAI-19) was held in Honolulu, Hawaii, on Sunday and Monday, January 27–28, 2019. There were fifteen workshops in the program: Affective Content Analysis: Modeling Affect-in-Action, Agile Robotics for Industrial Automation Competition, Artificial Intelligence for Cyber Security, Artificial Intelligence Safety, Dialog System Technology Challenge, Engineering Dependable and Secure Machine Learning Systems, Games and Simulations for Artificial Intelligence, Health Intelligence, Knowledge Extraction from Games, Network Interpretability for Deep Learning, Plan, Activity, and Intent Recognition, Reasoning and Learning for Human-Machine Dialogues, Reasoning for Complex Question Answering, Recommender Systems Meet Natural Language Processing, Reinforcement Learning in Games, and Reproducible AI. This report contains brief summaries of the all the workshops that were held.


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