An Architecture for Real-Time Reasoning and Learning

Computer, 1995

Annual Review in Automatic Programming, 1991

This essay is to point out some of the basic differences between conventional and real-time applications of AI and to provoke discussion on whether or not a new paradigm would facilitate better understanding of these differences.

Proceedings of the fourth …, 2000

In this paper we present AMSIA, an agent architecture that combines the possibility of using different reasoning methods with a mechanism to control the resources needed by the agent to fulfill its high level objectives. The architecture is based on the blackboard paradigm which offers the possibility of combining different reasoning techniques and opportunistic behavior. The AMSIA architecture adds a representation of plans of objectives allowing different reasoning activities to create plans to guide the ...

2002

The paper is an attempt to summarize the previous works of the author on integrating deductive and abductive reasoning paradigms for solving the classification task. A two-tiered reasoning and learning architecture in which Case-Based Reasoning (CBR) used both as a corrective of the solutions inferred by a deductive reasoning system and as a method for accumulating and refining knowledge is briefly described. As illustrative e~Amples the applications of the approach for problems of the case-bnsed maintenance of rnie-based systems and for case-based refinement of neural networks are presented.

2013

This paper presents an approach to the design of autonomous, real-time systems operating in uncertain environments. We address issues of problem solving and reflective control of reasoning under uncertainty in terms of two fundamental elements: l) a set of decision-theoretic models for selecting among alternative problem-solving methods and 2) a general computational architecture for resource-bounded problem solving. The decisiontheoretic models provide a set of principles for choosing among alternative problem-solving methods based on their relative costs and benefits, where benefits are characterized in terms of the value of information provided by the output of a reasoning activity. The output may be an estimate of some uncertain quantity or a recommendation for action. The computational architecture, called Schemer-ll, provides for interleaving of and communication among various problem-solving subsystems. These subsystems provide alternative approaches to information gathering, belief refinement, solution construction, and solution execution. In particular, the architecture provides a mechanism for interrupting the subsystems in response to critical events. We provide a decision theoretic account for scheduling problem-solving elements and for critical-event-driven interruption of activities in an architecture such as Schemer-II.

Abu Dhabi International Petroleum Exhibition & Conference, 2019

A real-time decision support solution for control room operators that targets increasing production efficiency by reducing plant upsets and disturbances has been developed. The solution relies on process engineering and plant knowledge combined with AI tools like ontology and rule-based reasoning. The aim is to enhance the basis for rapid and intelligent decision-making and increase human performance when abnormal situations occur. The solution is based on "Multilevel Flow Modeling" (MFM), which is a modeling language that builds on a systematic representation of relations between objectives and functions of plant equipment in a means-ends structure. The aim of MFM in this context is to develop models that allows for reasoning about causes and consequences of events, or upsets in process plants, such as oil and gas production facilities. A key feature of MFM is its compatibility with human cognition and results of MFM reasoning can therefore be communicated to operators in...

2002

The task at hand is the design and implementation of real-time agents that are situated in a changeful, unpredictable, and time-constrained environment. Based on Neisser's human cognition model, we propose an architecture for real-time agents. This architecture consists of three components, namely perception, cognition, and action, which can be realized as a set of concurrent administrator and worker processes. These processes communicate and synchronize with one another for real-time performance.

Robotics and Autonomous Systems, 2008

In this paper, we describe the principles and the methodologies that we have researched for the creation of a software infrastructure for bridging the gap from brain-like systems design to standard software technology. Looking at the brain, we constantly take inspiration and choose the relevant principles that our computer-base model should/could be based on. This ranges from the evolution of the brain (phylogenetically and ontogenetically), the inherent autonomy of the currently identified areas, the intrinsic synchronization through the most basic control mechanisms that regulates interaction, communication, and modulation. With these principles in mind, we started to make a subdivision of our system into instance, functional and computing architecture, modeling each sub-system with processes and tools in order to create a basic infrastructure that supports the research and creation of intelligent systems. The basic elements of our infrastructure are the BBCM (Brain Bytes Component Model) and BBDM (Brain Bytes Data Model), created to enable the modularization and reuse of our systems. Based on those, we have developed DTBOS (Design Tool for Brain Operating System), the design environment for supporting graphical design, RTBOS (Real-Time Brain Operating System), the middleware that supports real-time execution of our modular systems, and CMBOS (Control-Monitor Brain Operating System) to enable the monitoring of running modules. We will show the feasibility of the established environment by shortly describing some of the experimental systems in the area of cognitive robotics that we have created. This will serve to give a more concrete understanding of the dimensions and the type of systems that we have been able to create.

IBM Systems Journal, 2002

People communicate with each other in sentences that incorporate two kinds of information: propositions about some subject, and metalevel speech acts that specify how the propositional information is used-as an assertion, a command, a question, or a promise. By means of speech acts, a group of people who have different areas of expertise can cooperate and dynamically reconfigure their social interactions to perform tasks and solve problems that would be difficult or impossible for any single individual. This paper proposes a framework for intelligent systems that consist of a variety of specialized components together with logicbased languages that can express propositions and speech acts about those propositions. The result is a system with a dynamically changing architecture that can be reconfigured in various ways: by a human knowledge engineer who specifies a script of speech acts that determine how the components interact; by a planning component that generates the speech acts to redirect the other components; or by a committee of components, which might include human assistants, whose speech acts serve to redirect one another. The components communicate by sending messages to a Linda-like blackboard, in which components accept messages that are either directed to them or that they consider themselves competent to handle. In the years since its founding conference in 1956, the field of artificial intelligence (AI) has generated an impressive collection of valuable components, but no comparably successful architecture for assembling them into intelligent systems. As examples, the following list illustrates the range of AI components that were designed and implemented in the 1950s and 1960s:

2005

Reasoning with limited computational resources (such as time or memory) is an important problem, in particular in cognitive embedded systems. Classical logic is usually considered inappropriate for this purpose as no guarantees regarding deadlines can be made. One of the more interesting approaches to address this problem is built around the concept of active logics. Although a step in the right direction, active logics still do not offer the ultimate solution.

1998

The paper is an attempt to summarize the previous works of the author on integrating deductive and abductive reasoning paradigms for solving the classification task. A two-tiered reasoning and learning architecture in which Case-Based Reasoning (CBR) used both as a corrective of the solutions inferred by a deductive reasoning system and as a method for accumulating and refining knowledge is briefly described. As illustrative e~Amples the applications of the approach for problems of the case-bnsed maintenance of rnie-based systems and for case-based refinement of neural networks are presented.

Proceedings of the second international conference on Industrial and engineering applications of artificial intelligence and expert systems - IEA/AIE '89, 1989

Automation of the control of complex systems has been achieved through the application of computers using such tools as closed-loop control, finite-state machines, etc. However, a number of tasks in the control of such processes must still be performed by human operators, resisting conventional automation efforts. These tasks usually involve unforeseen circumstances, such as defective controller hardware or unusual behavior of the application being controlled. Operators often use experience or heuristic reasoning to cope with these types of process deviations. In this paper, we will describe the theory and design of a generic temporal/causal system called TEMPROS (TEMporal PROgramming System) used to perform intelligent real-time control, capable of assuming many of the responsibilities that are currently exclusively performed by human operators. The system uses temporal propositions as its reasoning mechanism, deviating from current temporal reasoning systems by adding the new state "potentially true" to the truth value of a proposition. In addition, the system employs a plan hierarchy and a "lazy instantiation" mechanism to achieve the performance needed to make intelligent decisions in real time. We shall also outline the application of TEMPROS to the domain of growing gallium arsenide crystals using the LEC process.

Over the last few years, the application of the agent/multiagent system paradigm seems appropriate for solving complex problems which require intelligence and bounded response times. This paper presents SIMBA: an architecture based on ARTIS agents as its main component for the development of real-time multiagent systems. The ARTIS agent architecture guarantees an agent response that satisfies all its critical temporal restrictions in a real-time environment. The main feature of SIMBA systems is their applicability for complex, distributed, real-time domains. The architecture allows the communication among agents taking into account their hard temporal restrictions. Also, the SIMBA architecture is open, allowing the interaction with external agents or FIPA-compliant agent platforms and offering temporallybounded services.

Artificial Intelligence in Real-Time Control 1994, 1995

Some of the theory-bound evolutional trends in real-time AI applications are pointed out based on analysis of essential properties of real-time systems as well as Al based systems. The evolutional mai~t~m is increasing inte~j~~plina~ intention. Three subtrends are illustrated on examples: mechanical combination of methods, Al methods used for approximate solution of "classical" problems, and abstract methods applied in new domains, In addition similarity between integrated circuits and real-time systems design and increased use of formal verification at the early stages of systems development are pointed out.

IAAI, 1990

This chapter describes the intelligent network controller assistant (INCA), an innovative system that shows that large-scale, real-time expert systems can be developed as a matter of course, on schedule, and with the same degree of reliability expected of conventional data processing systems. In developing this system, several more detailed innovative aspects were introduced. First, real-time performance is necessary for network control, which was achieved using standard (rather than specifically real-time adapted) hardware and operating systems. Second, the fault tolerance of the system is essential for such real-time control; so, INCA incorporates an online backup. Finally and perhaps most importantly, INCA is a new expert system application for a company's core business, with all the risks and visibility that this responsibility exposes INCA to. Therefore, reliability, efficiency, and usability were mandatory; this project could not hide behind descriptions such as "prototype" or "demonstration of principle." Other