Xem mẫu
Intelligent Agent-Based Cooperative Information Processing Model 17
The selected results may be incorrect, but as the evidences are accumulated, the true facts can be found eventually. Thus, the uncertainties are decreasing. The experienced rules and strategies to implement the selecting mechanism of a BOS are extremely important for improving the efficiencies.
The main tasks of the reasoning mechanism are to realize the cooperative problem solving, and according to the current defeasible logic structure (K,A), to carry out the assumption-based reasoning. That a heuristic conclusion P is derived from BOS means the conjunction of K and Acan derive P, and when contradiction is induced, A is ignored. Meanwhile, the reasoning mechanism calculates the “argument structure” and “environment” information for each derivative result and records them as a node, thus making a reasoning structural net. Furthermore, on the basis of the cooperative strategies, the reasoning mechanism should communicate the conclusions and the cooperative demands concerning the cooperation to the agents in other BOSs.
The major tasks of the distributed truth maintaining mechanism are to identify the contradictions in the reasoning structural net founded according to the reasoning mechanism and to remove the conflicts by means of cooperation among multiple agents to maintain the effectiveness of the reasoning. To identify contradictions is to check whether or not all kinds of constraint conditions comply with the rules. When contradictions are found and should be eliminated, not only all the nodes in their own BOS concerning the contradiction nodes must be updated, but also all the nodes concerning the changing nodes in other BOSs must be updated. This process is called the “related consistency for maintaining the cooperative reasoning struc-tural net.”
Therefore, in ACPS, the cooperative problem-solving procedure in MAS means that the agents in various BOSs select continually their own current defeasible logic structures, carry out cooperative reasoning according to these structures, maintain the distributed truth when any contradiction is derived, ignore the inconsistent assumption set, and select new defeasible logic structures to keep on reasoning. This process keeps on running repeatedly until the goals are attained. In this model, the key problems in cooperation are how to use effectively the experimental results of other BOSs to establish assumption, the maintenance and management of the assumptions, and how to eliminate rapidly the ill effects brought by the wrong conclusion propagations when contradictions appear.
It should be noted that: (1) the data structure of each BOS can maintain several incompatible assumption sets, but all the assumptions in (K, A) constituting the currently defeasible logic structures should be compatible. Only on these defeasible logic structures will the reasoning mechanism function, and just when contradictions appear in the solution, the inconsistent assumption sets are withdrawn and all their
Copyright © 2003, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited.
18 Yao & Zhang
related conclusions are eliminated; (2) the inconsistency may exist among the current assumption sets of various BOSs in the system, but they do not influence the effectiveness of the cooperative problem solving; and that is because the coopera-tive process is a mutual selecting process of each other and the cooperation are implemented when no contradictions are found in the current assumption sets of both sides.
DESIGNS AND IMPLEMENTATIONS OF ACPS WITH BOS MODEL IN THE DTIMS
DTIMS is implemented on a PC computer for distributed traveling situation assessment tasks. Its organization chart is seen in Figure 1. The DTIMS is composed of three BOSs. Each BOS represents an independent information processing subsystem composed of groups of agents, which is distributed on different physical locations and is linked with the other BOSs mutually in network. Thus, these BOSs can form hierarchy cooperative organizations, compute in parallel, and process information cooperatively. This section briefly introduces the basic structures of this system and then discusses the cooperative problem solving among the same level BOSs by means of ACPS.
Fundamental Definitions
In the traveling situation assessment problem solving, there may exist uncer-tainties or mistakes in the primary input information. Therefore, the problem-solving system must have a mechanism to maintain several possible situation models and to make the compatible models share the information so as to form the current situation-analyzing report. In the DTIMS, the ACPS method is used to realize the cooperative problem solving and implement the mechanism mentioned above.
In the DTIMS, all the information concerning the external environments and all the conclusions generated in interpreting and analyzing this information are repre-sented as proposition. They are classified in four types of propositions: precondi-tion, assumption, derivation, and communication.
The precondition proposition represents the pre-defined domain knowledge or generally correct propositions. Its truth remains constant during the problem solving. For example, the topographic knowledge and the features of the recogniz-able objects in the observing field are unchanged.
The assumption proposition indicates that there is no logic basis and it is supposed to be correct by the selecting mechanism in the system according to certain rules. The states of its truth may change during the successful procedure of
Copyright © 2003, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited.
Intelligent Agent-Based Cooperative Information Processing Model 19
problem solving. For example, the platform assumptions, expansion assumptions, and external assumptions defined in the DTIMS may change in the process of problem solving.
The derivation proposition means that all the conclusions are derived from other propositions according to the problem solving rules such as Expanding Rules, Fission Rules, Recognizing Rules, and so on. One important class of this kind is the inconsistent proposition. The appearance of this proposition in the situation model shows mistakes in the situation analysis. For example, that a space group is not recognized indicates there exists a mistake in the object assumption, and that a space group movement is incomplete indicates there are mistakes in the expansion assumption, and so on.
The communication proposition is one that determines to be communicated to the agent of other BOS in accordance with the cooperative problem-solving rules. The definition of this class of propositions is mainly used to realize the cooperative problem solving and the distributed truth maintaining.
Data Structure
The design of the data structures is extremely important to the assumption-based reasoning and has a direct influence to the problem solving efficiencies. In the DTIMS, each BOS has a Global Workspace Agent (GWA) who is a CFA and is in charge of managing shared data structures within the BOS. Their major structure, called the reasoning-workspace-area, is a complicated two-dimensional area showing the topographic information. According to the topographical positions, all the observing object information can be found. Whenever a proposition is derived in the system, a new node is founded in the reasoning structural net. Its contents are as follows:
[ node : node name;
node-type : proposition type;
node-content : proposition content; as-label : proposition label
owner : BOS’s name who derives this node; inference-description : inference rule descriptions; ante-list : antecedent node lists that derive this node;
conse-node-list : consequent node list whose deriving depend on this node; a-struc : argument structure of this node]
The argument structure of a node includes the following contents:
Copyright © 2003, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited.
20 Yao & Zhang
( node-time: founding time of this node; time: having observing time of this conclusion;
S: distance between the observing position and the center position of the BOS’s sensor;
agent-list: cooperative problem solving agent list; CF: times which this proposition has been proved)
All the derivative nodes are linked by pointers according to the deriving relations so as to form several inference tree structures, i.e., an inference structural net. On the bottom layer of this net is the two-dimensional array, reasoning-workspace-area, and the nodes located at the highest abstract level constitute the current derived situation model.
In the DTIMS, the intermediate results are classified. So, when they are referred to by topographic positions and result types, the system can ensure that the same propositions are related on the same nodes in the inference structural net, thus giving a full play to the assumption-based inference priorities.
Furthermore, by checking the constraint conditions, the system can find the contradictory states and then analyze the inconsistent assumption sets according to the contradiction types, the inconsistent context can be recognized and eliminated, and the assumption-based inference effectiveness is improved.
Basic Cooperative Problem Solving Algorithms
Algorithm implementations can be described from three aspects of selecting, reasoning, and truth maintaining.
The Selecting Mechanism
The object assumptions and the expansion assumptions are founded respec-tively by IFA and SAA in the problem solving process. The assumption-based problem solving tasks are generated simultaneously. The external assumptions are completed by HA. The main procedure for a assumption being founded is as follows:
• To check if there are same conclusions in the BOS’s inference structural net. • If there is a same conclusion in the GWA of this BOS, to increase the
creditability of this conclusion. Then, this procedure ends.
• To calculate respectively their argument structures. If the local conclusion is in contradiction with an external one, then according to a given rule, conclusions with greater argument structural creditability are selected. If the local argument structural creditability is greater, the external conclusion is
Copyright © 2003, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited.
Intelligent Agent-Based Cooperative Information Processing Model 21
discarded, and the procedure ends. If the external message has greater creditability, a type of truth-maintaining task is generated first, which with-draws the exiting conclusion, and then changes the external conclusion into an external assumption, to insert into the inference structural net, thus generating a problem-solving task based on this new assumption, and this procedure ends.
• If there is no same conclusion in the local BOS, the external conclusion is turned into an external assumption, which is then inserted in the inference structural net so that an assumption-based, problem-solving task is generated and then the procedure ends.
The Assumption — Based Inference Mechanism
The assumption-based inference mechanism is mainly completed by the IFA and SAA. The rules to calculate the assumption are explained as follows:
Set the assumption set of the conclusion P is AS(P) , and according to the definition:
If a AS(P), a supposes to be true and AS(P) is consistent, and so P is creditable;
If a AS(P), a is not creditable or AS(P) is inconsistent, then P is not creditable.
1. if P is the precondition proposition , then , AS(P) = {}.
2. if P is the assumption proposition, then, when P is an object assumption or an expansion assumption, AS(P) = {P};
when P is an external assumption, AS(P) = {BOS : P} AS (P), where
AS (P) is the assumption set of P in the original agent, and BOS : P denotes this external assumption from BOS.
3. If P is a derivation proposition, and a1 a2 an P, then
AS(P) ∪AS(aj ). j 1
4. If P is a communication proposition, the information of AS(P) will be used as the environmental information to be communicated to the corresponding cooperative agents together with P.
The problem solving of IFA and SAA includes the following abstract algorithm descriptive processes:
Copyright © 2003, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited.
...
- tailieumienphi.vn
nguon tai.lieu . vn