1. Concepts of Game Theory I

2. What are Multi-Agent Systems?
Organisational
relationship
Interaction
Agent
Spheres of
influence
Environment

3. A Multi-Agent System Contains:
A number of agents that
interact through communication
are able to act in an environment
have different “spheres of influence” (which may coincide)
will be linked by other (organisational) relationships.

4. Utilities of agents (1) Assume that we have just two agents:
AG = {i, j }
Agents are assumed to be self-interested:
They have preferences over environmental states

5. Utilities of agents (2)
Assume that there is a set of “outcomes” that agents have preferences over:
 = {1, 2, }
Example: odd-or-even game (alternative to head-or-tail)
 = {(0,0),…,(0,5),(1,0),…,(1,5),…(5,0),…,(5,5)}
These preferences are captured by utility functions:
ui :    uj :   
ueven((0,0)) = 1 ueven((0,1)) = 0 ueven((0,2)) = 1 …
uodd((0,0)) = 0 uodd((0,1)) = 1 uodd((0,2)) = 0 …
Or, more simply,
ueven((m,n)) = 1, if m +n is an even number; otherwise 0
uodd((m,n)) = 0, if m +n is an even number; otherwise 1

6. Utilities of agents (2)
Utility functions lead to preference orderings over outcomes:
 i ’ means ui ()  ui (’)
 j ’ means uj ()  uj (’)
But, what is utility?
In some domains, utility is analogous to money; e.g. we could have a relationship like this:
Utility
Money

7. Agent Encounters
To investigate agent encounters we need a model of the environment in which agents act:
agents simultaneously choose an action to perform,
the actions they select will result in an outcome   ;
the actual outcome depends on the combination of actions;
Assume each agent has just two possible actions it can perform:
C (“cooperate”)
D (“defect”).

8. The State Transformer Function
Let’s formalise environment behaviour as:
 : Aci  Acj  
Some possibilities:
Environment is sensitive to the actions of both agents:
 (D,D)  1  (D,C )  2  (C,D)  3  (C,C )  4
Neither agent has influence on the environment:
 (D,D)   (D,C )   (C,D)   (C,C )  1
The environment is controlled by agent j .
 (D,D)  1  (D,C )  2  (C,D)  1  (C,C )  2

9. Rational Action (1)
Suppose an environment in which both agents can influence the outcome, with these utility functions:
ui (1)  1 ui (2)  1 ui (3)  4 ui (4)  4
uj (1)  1 uj (2)  4 uj (3)  1 uj (4)  4
Including choices made by the agents:
ui ( (D,D))  1 ui ( (D,C ))  1 ui ( (C,D))  4 ui ( (C,C ))  4
uj ( (D,D))  1 uj ( (D,C ))  4 uj ( (C,D))  1 uj ( (C,C ))  4

10.  (C,C ) i  (C,D) i  (D,C ) i  (D,D)
Rational Action (2)
Then, the preferences of agent i are:
 (C,C ) i  (C,D) i  (D,C ) i  (D,D)
“C ” is the rational choice for i :
Agent i prefers outcomes that arise through C over all outcomes that arise through D.

11. Pay-off Matrices
We can charaterise this scenario (& similar scenarios) as a pay-off matrix : i
Defect
Coop 1 4 j
Agent i is the column player
Agent j is the row player

12. Dominant Strategies
Given any particular strategy s (either C or D) for agent i, there will be a number of possible outcomes
s1 dominates s2 if
every outcome possible by i playing s1
is preferred over
every outcome possible by i playing s2
A rational agent will never play a strategy that is dominated by another strategy
However, there isn’t always a unique strategy that dominates all other strategies…

13. Nash Equilibrium Two strategies s1 and s2 are in Nash Equilibrium if:
under the assumption that agent i plays s1, agent j can do no better than play s2; and
under the assumption that agent j plays s2, agent i can do no better than play s1.
Neither agent has any incentive to deviate from a Nash equilibrium!!
Unfortunately:
Not every interaction has a Nash equilibrium
Some interactions have more than one Nash equilibrium…
John Forbes Nash, Jr

14. Competitive and Zero-Sum Interactions
When preferences of agents are diametrically opposed we have strictly competitive scenarios
Zero-sum encounters have utilities which sum to zero:
   , ui ()  uj ()  0
Zero sum implies strictly competitive
Zero sum encounters in real life are very rare
However, people tend to act in many scenarios as if they were zero sum.

15. The Prisoner’s Dilemma
Two people are collectively charged with a crime
Held in separate cells
No way of meeting or communicating
They are told that:
if one confesses and the other does not, the confessor will be freed, and the other will be jailed for three years;
if both confess, both will be jailed for two years
if neither confess, both will be jailed for one year
Albert W. Tucker

16. The Prisoner’s Dilemma Pay-Off Matrix
Defect = confess; Cooperate = not confess
Numbers in pay-off matrix are not years in jail
They capture how good an outcome is for the agents
The shorter the jail term, the better
The utilities thus are:
ui (D,D)  2 ui (D,C )  5 ui (C,D )  0 ui (C,C )  3
uj (D,D)  2 uj (D,C )  0 uj (C,D )  5 uj (C,C )  3
The preferences are:
(D,C ) i (C,C ) i (D,D) i (C,D )
(C,D ) j (C,C ) j (D,D) j (D,C )

17. The Prisoner’s Dilemma Pay-Off Matrix
Defect
Coop 2 5 3
Defect = confess j
Coop = not confess
Top left: both defect, both get 2 years.
Top right: i cooperates and j defects, i gets sucker’s pay-off, while j gets 5.
Bottom left is the opposite
Bottom right: reward for mutual cooperation.