Class of Problems
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5 © Jaime Simão Sichman, 1998 Social Reasoning Multi-Agent Systems 6
© Jaime Simão Sii-Agent Systems
1
1
General Assumptions
Social Reasoning Multi-Agent Systems 12
When the agents are truly autonomous: I mutual dependence leads to cooperation, since both agents are aware that they depend on one another. Cheating is not a good strategy, because the goal is the same for both agents I reciprocal dependence leads to social exchange, and both agents will try to help the other to achieve his goal as means to achieve his own goal. Nevertheless, cheating may occur.
© Jaime Simão Sichman, 1998 Social Reasoning Multi-Agent Systems 11
I
I
© Jaime Simão Sichman, 1998
2
2
External Description
Considering an agent i, his external description entry for agent j is composed of: I G(j): set of j’s goals
Social Reasoning Multi-Agent Systems 8
© Jaime Simão Sichman, 1998
© Jaime Simão Sichman, 1998
Main Features of the SRM
I
Dependence Relations
Two class of dependence relations are defined: I unilateral relations: agent i depend on agent j for one of his goals g I bilateral relations: agents i and j depend respectively on one another for their goals g1 and g2 – mutual dependence: g1 is equal to g2 – reciprocal dependence: g1 and g2 are different
» simulation of social phenomena
– engineering perspective
» use the model in a class of problems
© Jaime Simão Sichman, 1998 Social Reasoning Multi-Agent Systems 2
Social Reasoning Multi-Agent Systems
© Jaime Simão Sichman, 1998
Social Interaction
I
Underlying Hypothesis
mentalistic approach – MAS for problem solving and MAS for social simulation [Castelfranchi 90] – symbolic vs. decision-theoretic approaches [Conte and Sichman 95] absence of domain specific on-line planning – case-based reasoning style an agent first chooses a goal, then a plan, and then the possible partners to whom a coalition proposal is to be sent [Sichman 96b]
9 © Jaime Simão Sichman, 1998 Social Reasoning Multi-Agent Systems 10
I
I
I
it is based on Social Power and Dependence Theory [Castelfranchi 90, Castelfranchi et al. 92] it enables to explain and predict the occurrence of social interactions, based on the agents’ complementarity its main idea is that agents are not auto-sufficient: they may depend on one another to achieve their own goals each agent has its own private external description, where the information about the others is stored
Social Reasoning Multi-Agent Systems 7
I
Auto-knowledge assumption – agents have knowledge about themselves, but beliefs about the others Consistency assumption – whenever an inconsistency is detected, agents choose a context in order to maintain a consistent model about the others – the decision model is based on the source of the information
– – – – recognition of a possible cooperation coalition formation plan formation coalition action
Social Reasoning
Therefore, an agent should have a social reasoning mechanism in order to react in such a scenario: I explicit representation of the others I explicit reasoning about the others – meta-level, domain independent mechanism I belief revision about the others – in an open scenario, the representation of the others is never correct and complete
© Jaime Simão Sichman, 1998 Social Reasoning Multi-Agent Systems 1
Motivation
The goal of this research is to develop na agent’s social reasoning mechanism: I choice of a theory as a starting point I formalise the theory I use the operational model with: – cognitive science perspective
Class of Problems
The future computer processing environments will have the following characteristics: I huge networks of processing resources – heterogeneous – autonomous – distributed I openness (no central design of the whole system) I remote execution of services These are the societies of objects [Tokoro 93] or the electronic organisations [Hewitt 93]
Social Reasoning Multi-Agent Systems 4
© Jaime Simão Sichman, 1998
Organisational Design
In such an open and dynamic scenario: I an organisation should be conceived dynamically I agents should be autonomous to choose whether they want to take part into an organisation or not We have adopted the cooperative problem solving model proposed in [Wooldridge and Jennings 94]:
© Jaime Simão Sichman, 1998 Social Reasoning Multi-Agent Systems 3
Class of Problems
In order to conceive such systems, one should assure:
I I I
I
the interconnection of its elements the interoperability of its elements the adaptation of its elements to possible changes in the environment, due to the dynamic entry and exit of services an operational model which could allow these elements to cooperate , if they want to
Multi-Agent Systems
Social Reasoning Dr. Jaime Simão Sichman University of São Paulo Computer Engineering Department jaime@p.br p.br/~jaime
I
General Assumptions
I
I
Non-benevolence assumption – agents are not benevolent – they adopt each others’ goals as a means to achieve their own goals – they are self-interested, but not necessarily selfish Sincerity assumption – agents do not lie – they can give false information, not deliberately
© Jaime Simão Sii-Agent Systems
1
1
General Assumptions
Social Reasoning Multi-Agent Systems 12
When the agents are truly autonomous: I mutual dependence leads to cooperation, since both agents are aware that they depend on one another. Cheating is not a good strategy, because the goal is the same for both agents I reciprocal dependence leads to social exchange, and both agents will try to help the other to achieve his goal as means to achieve his own goal. Nevertheless, cheating may occur.
© Jaime Simão Sichman, 1998 Social Reasoning Multi-Agent Systems 11
I
I
© Jaime Simão Sichman, 1998
2
2
External Description
Considering an agent i, his external description entry for agent j is composed of: I G(j): set of j’s goals
Social Reasoning Multi-Agent Systems 8
© Jaime Simão Sichman, 1998
© Jaime Simão Sichman, 1998
Main Features of the SRM
I
Dependence Relations
Two class of dependence relations are defined: I unilateral relations: agent i depend on agent j for one of his goals g I bilateral relations: agents i and j depend respectively on one another for their goals g1 and g2 – mutual dependence: g1 is equal to g2 – reciprocal dependence: g1 and g2 are different
» simulation of social phenomena
– engineering perspective
» use the model in a class of problems
© Jaime Simão Sichman, 1998 Social Reasoning Multi-Agent Systems 2
Social Reasoning Multi-Agent Systems
© Jaime Simão Sichman, 1998
Social Interaction
I
Underlying Hypothesis
mentalistic approach – MAS for problem solving and MAS for social simulation [Castelfranchi 90] – symbolic vs. decision-theoretic approaches [Conte and Sichman 95] absence of domain specific on-line planning – case-based reasoning style an agent first chooses a goal, then a plan, and then the possible partners to whom a coalition proposal is to be sent [Sichman 96b]
9 © Jaime Simão Sichman, 1998 Social Reasoning Multi-Agent Systems 10
I
I
I
it is based on Social Power and Dependence Theory [Castelfranchi 90, Castelfranchi et al. 92] it enables to explain and predict the occurrence of social interactions, based on the agents’ complementarity its main idea is that agents are not auto-sufficient: they may depend on one another to achieve their own goals each agent has its own private external description, where the information about the others is stored
Social Reasoning Multi-Agent Systems 7
I
Auto-knowledge assumption – agents have knowledge about themselves, but beliefs about the others Consistency assumption – whenever an inconsistency is detected, agents choose a context in order to maintain a consistent model about the others – the decision model is based on the source of the information
– – – – recognition of a possible cooperation coalition formation plan formation coalition action
Social Reasoning
Therefore, an agent should have a social reasoning mechanism in order to react in such a scenario: I explicit representation of the others I explicit reasoning about the others – meta-level, domain independent mechanism I belief revision about the others – in an open scenario, the representation of the others is never correct and complete
© Jaime Simão Sichman, 1998 Social Reasoning Multi-Agent Systems 1
Motivation
The goal of this research is to develop na agent’s social reasoning mechanism: I choice of a theory as a starting point I formalise the theory I use the operational model with: – cognitive science perspective
Class of Problems
The future computer processing environments will have the following characteristics: I huge networks of processing resources – heterogeneous – autonomous – distributed I openness (no central design of the whole system) I remote execution of services These are the societies of objects [Tokoro 93] or the electronic organisations [Hewitt 93]
Social Reasoning Multi-Agent Systems 4
© Jaime Simão Sichman, 1998
Organisational Design
In such an open and dynamic scenario: I an organisation should be conceived dynamically I agents should be autonomous to choose whether they want to take part into an organisation or not We have adopted the cooperative problem solving model proposed in [Wooldridge and Jennings 94]:
© Jaime Simão Sichman, 1998 Social Reasoning Multi-Agent Systems 3
Class of Problems
In order to conceive such systems, one should assure:
I I I
I
the interconnection of its elements the interoperability of its elements the adaptation of its elements to possible changes in the environment, due to the dynamic entry and exit of services an operational model which could allow these elements to cooperate , if they want to
Multi-Agent Systems
Social Reasoning Dr. Jaime Simão Sichman University of São Paulo Computer Engineering Department jaime@p.br p.br/~jaime
I
General Assumptions
I
I
Non-benevolence assumption – agents are not benevolent – they adopt each others’ goals as a means to achieve their own goals – they are self-interested, but not necessarily selfish Sincerity assumption – agents do not lie – they can give false information, not deliberately