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RETSINA: A Distributed Multi-Agent Infrastructure for Information Gathering and Decision Support The Robotics Institute Carnegie Mellon University PI: Katia Sycara http://www.cs.cmu.edu/~sycara http://www.cs.cmu.edu/~softagents Talk Outline Motivation RETSINA Infrastructure

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retsina a distributed multi agent infrastructure for information gathering and decision support

RETSINA: A Distributed Multi-Agent Infrastructure for Information Gathering and Decision Support

The Robotics Institute

Carnegie Mellon University

PI: Katia Sycara

http://www.cs.cmu.edu/~sycara

http://www.cs.cmu.edu/~softagents

talk outline
Talk Outline
  • Motivation
  • RETSINA Infrastructure
  • Capability-Based Coordination
  • Middle Agents
  • RETSINA Applications
  • Experimental Results
  • Conclusions
features of mas
Features of MAS
  • Multiple agents through communication networks
  • Local views - no agent has sufficient information or capabilities to solve problems alone
  • Decentralized control - no “master agent”
  • Decentralized data - no global data storage
  • Agent Coupling - balancing computation and communication
  • Asynchronous - multiple activities operating in parallel
basic problems of multi agent systems
Basic Problems of Multi-Agent Systems
  • Coordination in an open environment
  • Asynchronous agent operation
  • Distributed resource allocation
  • Distribution of tasks
  • Interoperability of agents
  • Privacy concerns
  • Persistent goal-directed behavior
  • Overall system stability
  • Conflicts (resolution, avoidance)
agents transacting in open environments
Agents Transacting in Open Environments

Two phases:

  • Locating appropriate agents
    • through different kinds of middle agents
  • Performing the transaction
    • with or without middle agents
issues with locating agents 1
Issues with Locating Agents (1)
  • Evaluation criteria
    • performance
    • robustness
    • scalability
    • load balancing
    • privacy
  • Where the matching is done
    • At the requester (preserving the privacy of requesters)
    • middle agents
    • service providers
issues with locating agents 2
Issues with Locating Agents (2)
  • Information needed to feed the “matching engine”
    • Requester can provide request for service, with or without service-related preferences (e.g., cost, quality)
  • Output
    • Unsorted list of contact info
    • Sorted list of contact info
    • given to

requester

provider

    • Input kept at middle agent to be fed into transaction phase
transaction phase
Transaction Phase
  • Providers and requesters interact with each other directly
    • a negotiation phase to find out service parameters and preferences (if not taken into account in the locating phase)
    • delegation of service
  • Providers and requesters interact through middle agents
    • middle agent finds provider and delegates
    • hybrid protocols
  • Reasons for interacting through middle agents
    • privacy issues (anonymization of requesters and providers)
    • trust issues (enforcement of honesty; not necessarily keep anonymity of principals); e.g. NetBill
protocols
Protocols
  • Who to talk to: principals involved
  • Message content:
    • ex: a LARKS specification
  • Local processing:
    • ex: implied by KQML performatives (service-request, request-for-service-providers)
matching engine for service providers requesters
Matching Engine for Service Providers & Requesters

sorted list of agent contact info

unsorted list of agent contact info

decision algorithm

matching capabilities with requests

(LARKS)

matching capabilities with requests

(LARKS)

service request

+ parameters

service request

capability parameters

capability parameters

slide11

Broadcaster

Request for service

Requester

Broadcaster

Broadcast

service request

Offer of service

Delegation of service

Results of

service request

Provider 1

Provider n

slide12

Yellow Page

Request for service

Requester

Yellow Page

Unsorted list of contact info

of (P1,P2, …, Pk)

Advertisement

of capabilities

Delegation of service

Results of

service request

Provider 1

Provider n

matchmaking
Matchmaking

Request for service

Requester

Matchmaker

Unsorted full description

of (P1,P2, …, Pk)

Advertisement

of capabilities

+para.

Delegation of service

Results of

service request

Provider 1

Provider n

classified ads
Classified Ads

Requester 1

Request for service+pref.

Classified Ads

Request for service+pref.

Advertisement

of capabilities

(R1,R2, …, Rk)

contact info.

Requester n

Offer of service

Provider

selects

requester

Delegation of service

Provider 1

Service results

slide15

Recommender

Request for service+pref.

Requester

Recommender

Sorted full description

of (P1,P2, …, Pk)

Advertisement

of capabilities

+para.

Delegation

of service

Results of

service request

Provider 1

Provider n

slide16

FacilitatorCombines Agent Location and Transaction Phases

Request for service+pref.

Requester

Facilitator

Results of service

Advertisement

of capabilities

+ para.

Service

result

Delegation

of service

Provider 1

Provider n

brokering
Brokering

Delegation of service

+ preferences

Requester

Broker

Results of service

Advertisement

of capabilities

+ para.

Delegation

of service

Results

of service

Provider 1

Provider n

contract net
Contract Net

Request for service

+ preferences

Requester

Manager

Results of service

Delegation

of service

Broadcast service

request + pref

Broadcast

Results of

Service

Offer

of service

Broadcast

Offer

of service

Provider 1

Provider 2

Provider n

motivation for multi agent systems
Motivation for Multi Agent Systems
  • Global Information and Markets
  • Increasingly networked world
  • Vast quantities of unorganized information
  • Diverse and distributed information sources
  • Moving from locating documents to making decisions
conclusions
Conclusions
  • Agent-based software development is an emerging paradigm
  • Agent societies that parallel human societies
  • Agent society as a unit of intelligence
  • Implications of agent societies for human workplace and institutions
  • Challenges
    • Overall system (humans + agents) predictability
    • Integration of legacy systems
    • Security, privacy and trust issues