Blackboard Model Of Problem Solving Research Articles

Concurrent marketing analysis: a multi‐agent model for product, price, place and promotion

Marketing management presents challenging ground for the integrated use of intelligent agents. The design of a strategic marketing plan presents a natural division of four distinct yet independent decision problems. Concurrent execution of these four functions can yield a significant decrease in time‐to‐market for new products, and turnaround time for modified products. Electronic information is a two‐edged sword. On the one hand, it results in information overload, taxing the decision‐ making process. On the other hand, the electronic nature of these vast information flows makes them accessible to intelligent agents who can improve the decision‐making process. This paper presents the problem of information overload and decision‐making complexity in marketing management. In it, we present a blackboard‐based agent architecture that allows individual agents to proceed toward their given goals yet react opportunistically to developments reported by other marketing agents. We present the blackboard model of problem solving, and discuss why it is well suited to support multiple marketing agents. CMA, a multi‐agent model for concurrent marketing analysis, is discussed and the agent architecture required for creating a cooperating society of marketing agents is presented.

The concurrent language, Shared Prolog

Shared Prolog is a new concurrent logic language. A Shared Prolog system is composed of a set of parallel agents that are Prolog programs extended by a guard mechanism. The programmer controls the granularity of parallelism, coordinating communication and synchronization of the agents via a centralized data structure. The communication mechanism is inherited from the blackboard model of problem solving. Intuitively, the granularity of the logic processes to be elaborated in parallel is large, while the resources shared on the blackboard can be very fined grained. An operational semantics for Shared Prolog is given in terms of a distributed model. Through an abstract notion of computation, the kinds of parallelism supported by the language, as well as properties of infinite computations, such as local deadlocks, are studied. The expressiveness of the language is shown with respect to the specification of two classes of applications: metaprogramming and blackboard systems.

AN OVERVIEW OF CASSANDRA‐II

A brief non‐technical overview of the CASSANDRA‐II system is presented. The system performs knowledge‐based monitoring of aircraft movements in controlled airspace, and reports violations of air traffic control rules to the operator. The system is based on the blackboard model of problem solving, but differs in the relative autonomy of its abstraction levels. Abstraction levels, in CASSANDRA‐II, are equipped with control components which are responsible for scheduling all decisions based on the level contents. The system is designed for continuous real‐time operation; in this context, it is important that computer memory does not become full and halt the execution of the system. CASSANDRA‐II contains special‐purpose, knowledge‐based mechanisms for the removal of out‐dated blackboard information.

Blackboard Application Systems, Blackboard Systems and a Knowledge Engineering Perspective

The first blackboard system was the Hearsay-II speech-understanding system (Erman et al. 1980), which evolved between 1971 and 1976. Subsequently, many systems have been built that have similar system organization and run-time behavior. The objectives of this document (a part of a retrospective monograph on the AGE Project currently in preparation) are (1) to define what is meant by blackboard systems and (2) to show the richness and diversity of blackboard system designs. In Part 1 we discussed the underlying concept behind all blackboard systems -- the blackboard model of problem solving. In order to bridge the gap between the model and working systems, we introduced and discussed the blackboard framework. We also traced the history of ideas and designs of some application systems that helped shape the blackboard model. In Part 2, we describe and contrast existing blackboard systems. Blackboard systems can generally be divided into two categories: application systems and skeletal systems. In application systems, the blackboard system components are integrated into the domain knowledge required to solve the problem at hand.

The blackboard model of problem solving

The blackboard model of problem solving

The blackboard model of problem solving

The first system was the HEARSAY-II speech understanding system (Erman et al.,1980) that evolved between 1971 and 1976. Subsequently, many have been built that have similar system organization and run-time behavior. The objectives of this article are (1) to define what is meant by blackboard systems and (2) to show the richness and diversity of system designs. The article begins with a discussion of the underlying concept behind all systems, the model of problem solving. In order to bridge the gap between a model and working systems, the framework, an extension of the basic model is introduced, including a detailed description of the model's components and their behavior. A model does not come into existence on its own, and is usually an abstraction of many examples. In Section 2 the history of ideas is traced, and the designs of some application that helped shape the model are detailed. Part 2 of this article which will appear in the next issue of AI Magazine, describes and contrasts some and discusses the characteristics of application problems suitable for the method of problem solving.