Behavioural Science – Part 2

Global Sourcing IT Industry

Mahmudur Rahman Manna ^[ref]

(if you have not read the part 1)

Team Formation and current practices:

Gaming World: Multi Agent System (Markov Decision Process)

In game theory, a discussed topic is Multi Agent Systems along with Markov decision process. Agent is an autonomous entity that acts in the world, interacting with its environment and with other agents. It can be a human, a robot, a software process etc. One of the key ideas behind this approach is that several different agents can cooperate to achieve certain goals. This requires the design of efficient collaboration protocols, of which team formation is a typical example.

Cooperative behaviour, which is one of the greatest advantages of agent based computing, has been studied from many different angles over the years. Coalitional games have traditionally been analysed from a game-theoretic perspective, but in recent years have attracted a lot of attention from researchers in artificial intelligence, especially in cooperative task completion. Several approaches for team formation and collaborative task solving have been considered including team formation under uncertainty using simple heuristic rules, reinforcement learning techniques and methods using distributed graph algorithms. To reason formally about cooperative games, several logics (e.g., Alternating Time Logic, Coalitional Game Logic, Strategy Logic) and other formalisms (e.g., Cooperative Boolean Games) have been introduced and used to analyse coalitional behaviour

This theory introduces definitions of:

-          Agent organisations,
-          Tasks,
-          Teams,
-          Rewards (to measure the performance of both individual agents and agent teams).

Furthermore this theory has now several developed algorithms and models for verifications. Off course those are to improve how we can derive more efficient and effective, near perfect results/successes.

Relevance of introducing this topic is clearer for the similarities it has with our multi provider and vendor oriented developments. In our case it’s not system or robot rather it’s us. A consciousness driven being whose self-esteem is highly counted to him/her rather than any team success and organisation gain if not it merges or matches with his/her self-esteem.  

Its better we are already dealing with intelligent and social being, who usually loves to be in team. But also we know about lots of wars the world has seen. So the dynamics of team is really complex part to keep in a steady mode and surely if there is no such mentor body to take care of that.

But the interesting part of Markov Decision Process (MDP) is its ‘reward’ part that really counts also in human cases.

MDP has four key things:

1.       State
2.       Action
3.       Probability of an  action to be in a state at a certain time
4.       Reward

And reward comes when an action achieves a certain state. 

                                                                   

                                                                 Figure 6: MDP (‘S’ refers State and ‘a’ refers action)

There is much implication of MDP in our multi provider based project development. Our try will be to relate team dynamics and MDP core concepts to bring on a table and analyse how it can help in having a better environment for individuals who are dwelling in heterogeneous provider based platform.   

References

John B. Miner, ORGANIZATIONAL BEHAVIOR Foundations, Theories, and Analyses, OXFORD UNIVERSITY PRESS, 2002

Stephen P. Robbins, ORGANIZATIONAL BEHAVIOR, Prentice Hall International, Inc.

Fonstad, Nils, and Robertson, Engaging for Change: An Overview of the IT Engagement Model, CISR Research Briefing, Sloan School of Management, Massachusetts Institute of Technology (MIT), March 2005.

 Craig Schiff, Engagement Management is Key to Implementation Success, http://www.information-management.com/issues/20040401/1000840-1.html , November, 6^th 2011.

Dr. Z , Business of Stress: Rise of the Type A Machines, http://www.stresshacker.com/2010/01/business-of-stress-rise-of-the-type-a-machines/, November, 6^th 2011.

Donald Bell, UML basics: The component diagram, http://www.ibm.com/developerworks/rational/library/dec04/bell/, November, 6^th 2011.

Ilan Oshri and Julia Kotlarsky, Special Issue on Global Sourcing: IT Services, Knowledge and Social Capital, http://www.palgrave-journals.com/jit/journal/v23/n1/full/2000129a.html#bib7 , November, 6^th 2011.

Taolue Chen, Marta Kwiatkowska, David Parker, and Aistis Simaitis, Verifying Team Formation Protocol with Probabilistic Model Checking, Department of Computer Science, University of Oxford, July 2011.

Frank Dignum, Dialogue in team formation: a formal approach, Faculty of Mathematics and Computing Science, Technical University Eindhoven.

Jos´e M Vidal, Fundamentals of Multiagent Systems with NetLogo Examples, University of South Carolina, March 2009.

S. Abdallah and V.R. Lesser. Organization-based cooperative coalition formation. In IAT, pp. 162–168. IEEE, 2004.

Roderick van cann, slinger jansen and sjaak brinkkemper, Team Composition in Distributed software development, universiteit Utrecht