Agent, method and computer system for negotiating in a virtual environment

• US 20060020565A1
• Filed: 02/03/2003
• Published: 01/26/2006
• Est. Priority Date: 02/04/2002
• Status: Active Grant

• Current Assignee: Magenta Corp. Ltd.
• Original Assignee: Magenta Corp. Ltd.
• Inventors: Skobelev, Peter, Rzevski, George
• Granted Patent: US 7,562,002 B2
• Time in Patent Office: Days
• US Class Current: 706/50
• CPC Class Codes: G06F 2209/503 Resource availability
• CPC Class Codes: G06F 9/5027 the resource being a machine, e.g. CPUs, Servers, Terminals

Abstract

A multi-agent system is described that uses software agents to represent objects in a chosen real world environment. Each agent has structure having certain characteristics where a relation with other agents can be established if the other agents have characteristics that are suitable to the requesting agent. The multi-agent system is able to perform dynamic negotiations autonomously between agents so as to establish relations when a new event enters the system or to offer compensation to modify existing relations and to self-organise to optimise the overall value of the system.

Claims

1. An agent adapted for negotiating in a virtual environment, the agent comprising:

an agent descriptor implemented as an executable program and comprising a set of properties which determine the negotiating characteristics of the agent; and

an agent body implemented as an executable program and comprising at least one sensor for receiving information from the virtual environment, at least one actuator for interacting with the environment, and a decision engine operable in an active state during a predetermined time period to execute a decision making process based on the information received from the at least one sensor wherein the decision engine is operable to establish a relation with another agent in dependence on the negotiating characteristics and to determine a value representing the quality of the established relation.

2. An agent according to claim 1, wherein at least some of said properties are associated with a set of attributes which define the nature of the agent.

3. An agent according to claim 1 wherein at least some of said properties each refer to a set of scenarios, each scenario comprising a sequence of commands that govern the behaviour of execution of the agent.

4. An agent according to claim 3, wherein said decision engine is operable to select from said set of scenarios the scenario considered to be most appropriate based on the information received from the at least one sensor according to the negotiating characteristics of the agent and the quality of any existing established relation that the agent has made.

5. An agent according to claim 1, wherein the virtual environment represents a real environment including demands and resources, and wherein said agent is a demand agent allocated to a real demand.

6. An agent according to claim 1, wherein the virtual environment represents a real environment including demands and resources, and wherein said agent is a resource agent allocated to a real resource.

7. An agent according to claim 1, wherein the agent body comprises a scene memory holding data representing the current state of the virtual environment.

8. An agent according to claim 3 wherein one of said scenarios is configured to cause the decision engine to disturb an established relation between a pair of agents by offering compensation which will improve said value.

9. An agent according to claim 1, wherein the agent body comprises ontology memory holding knowledge relating to the nature of the agent.

10. An agent according to claim 3, wherein the agent body comprises command memory for holding said scenarios.

11. An agent according to claim 1, wherein the at least one sensor comprises means for reading accessible database fields.

12. An agent according to claim 1, wherein the at least one sensor comprises a mailbox mechanism for receiving messages.

13. An agent according to claim 1, wherein the at least one actuator comprises means for accessing a database to update data fields therein.

14. An agent according to claim 1, wherein the actuator comprises means for despatching a message.

15. An agent according to claim 1, wherein the agent body comprises a timer for controlling said predetermined time period.

27. An agent according to claim 1 having ontology memory for storing knowledge concerned with the characteristics of and relations between agents in a multi-agent system, wherein an agent is able to refer to its ontology memory to find a list of suitable agents with which to negotiate.

28. An agent according to claim 27, wherein said ontology memory contains common knowledge which is accessible by all agents in a multi-agent system and private knowledge which can only be accessed by said agent.

29. An agent according to claim 27, wherein said characteristics of an agent comprise properties, attributes and values.

30. An agent according to claim 27, wherein said ontology memory is domain specific so that an agent may be specially imbued with the knowledge of a particular application.

31. An agent according to claim 30, wherein said application is a logistics application.

16. A method of simulating a real environment by creating a virtual environment comprising a plurality of agents, the method comprising:

for at least some of said agents, invoking an active state of the agent for a predetermined time period;

for each active agent, implementing a decision making process based on information received from at least one sensor according to negotiating characteristics of the agent to determine whether a relation can be established with another agent; and

after said predetermined time period invoking a passive state of the agents, wherein said agents have a free or paired status and wherein paired agents hold a value determining the quality of the relation they have established.

17. A method of operating a computer to implement an agent adapted for negotiating in a virtual environment, the method comprising:

executing a first program defining an agent descriptor comprising a set of properties which determine the negotiating capability of the agent;

setting up an agent body by providing at least one sensor for receiving information from the virtual environment and at least one actuator for interacting with the environment; and

executing a second program to implement a decision engine associated with said at least one sensor, said decision engine being operable in an active state during a predetermined time period to execute a decision making process based on the information received from the at least one sensor according to the negotiating characteristics of the agent wherein the decision engine is operable to establish a relation with another agent in dependence on the negotiating characteristics and to determine a value representing the quality of the established relation.

18. A method according to claim 17, which comprises loading into a command memory a set of scenarios to which at least some of said properties refer, each scenario comprising a different set of commands.

19. A method according to claim 18, wherein said decision making process selects the most appropriate scenario from a set.

20. A method according to claim 17, which comprises compiling in a scene memory a current scene of the virtual environment for access by the agent.

21. A method according to claim 20, wherein the current scene is altered on the arrival of a new event and if the event is important then the decision making process selects a different scenario.

22. A method according to claim 21, wherein said new event is a new agent.

23. A method according to claim 21, wherein said new event is a message from an existing agent in the scene.

24. A method according to claim 21, wherein if a new event enters the scene but the event is not important then the decision making process continues to execute the current scenario.

25. A method of operating a computer system to manage demands and resources, the method comprising:

generating a scene representing the current state of resources and demands;

instantiating a plurality of agents as executable programs, including a first set of resource agents representing resources and a second set of demand agents representing demands, wherein each agent is operable to exchange messages with another agent and comprises a decision engine for executing a decision making process based on information from the scene and messages from said other agent to implement a relation with said other agent and to associate a relation value with said relation; and

comparing that relation value with a reference value for the relation to determine whether the relation is satisfactory or not.

26. A computer system configured as a virtual world representing a real world, the system comprising:

a first set of demand agents implemented as executable programs, each comprising a set of properties representing demands in the real world;

a second set of resource agents implemented as executable programs, each comprising a set of properties representing resources in the real world;

wherein the demand agents and the resource agents are operable to negotiate by exchanging messages, said messages containing said sets of properties corresponding to the demands and resources of each agent so that a decision engine can establish a relation based on predefined criteria; and

wherein when a new demand or resource enters the system, an agent representing the new demand or resource is able to disturb an established relation between a pair of agents by offering compensation to improve a value representing the quality of the established relation.

32. A computer system comprising a processor for executing a plurality of programs, each program represents an agent for negotiating in a virtual environment and a memory which stores a plurality of agent definers, each agent definer having an ontology comprising:

a set of properties defining the nature of the agent;

a set of attributes defining characteristics used for negotiating purposes by the agent;

a set of scenarios executable by the agent to implement different decision making processes; and

a relation quality store for holding a value defining the quality of a relation established by the agent.