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Decision-Making Techniques By: James Delk

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Decision-Making Techniques. By: James Delk. What are Decision-Making Techniques(DMTs)?. - PowerPoint PPT Presentation

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Page 1: Decision-Making Techniques

Decision-Making Techniques

By: James Delk

Page 2: Decision-Making Techniques

What are Decision-Making Techniques(DMTs)?

Decision making is the study of identifying and choosing alternatives based on the values and preferences of the decision maker. Making a decision implies that there are alternative choices to be considered, and in such a case we want not only to identify as many of these alternatives as possible but to choose the one that best fits with our goals, objectives, desires, values, and so on.. (Harris (1980))

Figure 1[1]

Page 3: Decision-Making Techniques

What are DMTs cont.

“Decision making techniques fall into three major categories: random; intuition based; or analytical. ”[2]

Page 4: Decision-Making Techniques

Requirements

Apples to oranges? Assigning values

Figure 2[3]

Page 5: Decision-Making Techniques

DMT Setup Define the problem Determine requirements Establish goals Identify alternatives Define criteria Select the method to be used Evaluate against criteria Validate against problem[4]

Page 6: Decision-Making Techniques

Why use DMTs

Physical representation of options

Double check variables Future reference Presentations Standard of measurement “if you don’t know where

your going it doesn’t matter which way you go”(Lewis Carroll)

Figure 3[5]

Page 7: Decision-Making Techniques

DMT Example

question/decision/option:

pros (for - advantages)

scorecons (against - disadvantages)

score

       

       

       

       

       

       

       

       

totals   totals  

Pros vs. Cons (weighted)

Figure 5[6]

Page 8: Decision-Making Techniques

DMT ExampleAnalytic Hierarchy Process

Figure 6[2]

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DMT ExampleSimple Decision Tree

Figure 7[2]

the number of possible decision trees is exponential in the number of attributes

Page 10: Decision-Making Techniques

DMT ExampleSimple Influence Diagram

Figure 8[2]

Page 11: Decision-Making Techniques

DMT ExampleLinear Programming

Figure 9[7]

Page 12: Decision-Making Techniques

Computer Science?

AI Databases Programmi

ng System

design Neural

networks

Figure 10[8]

Page 13: Decision-Making Techniques

Computer Science cont.

System architecture

Figure 11[8]

Page 14: Decision-Making Techniques

Game Theory Game theory is "the study of mathematical

models of conflict and cooperation between intelligent rational decision-makers.“[9]

A BA –1, 1 3, –3B 0, 0 –2, 2

Zero-sum gain game theory

Figure 12[9]

Page 15: Decision-Making Techniques

Multi Agent Systems A multi-agent system (MAS) is a system composed of

multiple interacting intelligent agents within an environment.[10]

Multi-agent systems are dependent upon a theoretical base that is provided through game theory.

Multi-agent system

Figure 13[10]

Page 16: Decision-Making Techniques

MAS cont. Allowing

multiple units to break down computations to the easiest level for completion by many different agents

Figure 14[11]

Page 17: Decision-Making Techniques

Game theory sample code

''' Approximate the strategy oddments for 2 person zero-sum games of perfect information. Applies the iterative solution method described by J.D. Williams in his classic book, The Compleat Strategyst, ISBN 0-486-25101-2. See chapter 5, page 180 for details. ‘'' from operator import add, neg def solve(payoff_matrix, iterations=100): 'Return the oddments (mixed strategy ratios) for a given payoff matrix' transpose = zip(*payoff_matrix) numrows = len(payoff_matrix) numcols = len(transpose) row_cum_payoff = [0] * numrows col_cum_payoff = [0] * numcols colpos = range(numcols) rowpos = map(neg, xrange(numrows)) colcnt = [0] * numcols rowcnt = [0] * numrows active = 0 for i in xrange(iterations): rowcnt[active] += 1 col_cum_payoff = map(add, payoff_matrix[active], col_cum_payoff) active = min(zip(col_cum_payoff, colpos))[1] colcnt[active] += 1 row_cum_payoff = map(add, transpose[active], row_cum_payoff) active = -max(zip(row_cum_payoff, rowpos))[1] value_of_game = (max(row_cum_payoff) + min(col_cum_payoff)) / 2.0 / iterations return rowcnt, colcnt, value_of_game

Figure 15[12]

O((m+n)*iterations

Page 18: Decision-Making Techniques

Example AI processIBM’s Watson AI’s decision processhttp://www.youtube.com/watch?v=cU-AhmQ363I

Figure 16[13]

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References [1] hhttp://chamonixvue.wordpress.com/2012/02/06/decision-making/ [2] http://www.decision-making-solutions.com/decision_making_techniques.html [3]http://blogs.helsinki.fi/dervin/2012/03/13/cfp-appels-and-oranges/ [4] Fülöp, J.: Introduction to Decision Making Methods. Working Paper 05-6,

Laboratory of Operations Research and Decision Systems, Computer and Automation Institute, Hungarian Academy of Sciences, Budapest, November 2005

[5]http://djcase.com/case-in-point/ginny-wallace/structured-decision-making-common-sense-made-explicit

[6] http://www.businessballs.com/problemsolving.htm [7]http://www.cs.duke.edu/courses/spring08/cps296.2/ [8]http://www.ece.ubc.ca/sites/default/files/Falessi%202011%20CSUR.pdf [9] http://en.wikipedia.org/wiki/Game_theory [10] http://en.wikipedia.org/wiki/Multi-agent_system [11]http://fofoa.blogspot.com/2012/02/superorganism-open-forum.html [12]

http://code.activestate.com/recipes/496825-game-theory-payoff-matrix-solver/ [13] http://en.wikipedia.org/wiki/File:DeepQA.svg