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Rule-based expert systems: The mycin experiments of the stanford heuristic programming project: B.G. Buchanan and E.H. Shortliffe, (Addison-Wesley, Reading.
Table of contents

In the talk, after shortly describing the s-bots hardware and the methodology we followed to develop algorithms for their control, I will focus on the capabili- ties of the swarm-bot robotic system by showing video recordings of some of the many experiments we performed to study coordinated movement, path formation, self-assembly, collective transport, shape formation and reconfiguration, distri- buted fault detection and other collective behaviors. Brief Bio Prof.

The unit is a center of excellence appointed by the Academy of Finland. In the center, Honkela is the head of the Computational Cognitive Systems research group.

Earlier he has served as a professor at the laboratory of computer and information science at TKK and as a professor at the Media Lab of University of Art and Design Helsinki. Honkela has approximately one hundred scientific publications. He has conducted research on several areas related to artificial and computational intelligence, cognitive modeling and natural language processing including a central role in the development of the Websom method for visual information retrieval and text mining based on the Kohonen self-organizing map algorithm.

He has been in a responsible position for a large number of scientific conferences and workshops. Abstract It is commonplace to view autonomous agents by considering how much freedom they exhibit in their goal-directed behavior.

Duplikatsitater

In other words, the level of motivational autonomy is then in focus. In this presentation, I will discuss, however, why and how the conceptual autonomy of agents is another crucial issue in the field of multiagent system development. In many systems, the agents are provided with a shared conceptual ground. This poses severe limitations for the autonomy of the agents. Namely, it is a reasonable requirement that autonomous agents should be able to interact with each other robustly in open-ended changing environments.

As each agent has its own developmental history and as the environments vary to some extent from agent to agent, it is necessary for each agent to build a model of its environment in an individual manner. On the other hand, the agents need to compare these models with each other to enable shared conceptual ground. This can realistically take place through communication in partially shared contexts leading into a sufficient convergence of mapping between the language used by the agents and their individual conceptual systems. In the presentation, I will also discuss what kind of implications these considerations have for the area of artificial intelligence in general.

Brief Bio Dr. Augusto's research experience since has been focused on AI-related problems with emphasis on temporal reasoning. His latest research activities have explored the application of spatio-temporal reasoning to Ambient Intelligence AmI in general and Smart Homes in particular.

Knowledge bases and generative models

Abstract Ambient Intelligence is growing fast as a multi-disciplinary area which promises to have a real beneficial influence in our society and to revolutionize the way people interacts with computing. The basic idea is that by enriching an environment with technology sensors and devices interconnected through networks , a Smart Environment, systems can be built such that information gathered in real-time and historical data accumulated can be used to support decisions that benefit the users of that environment.

An examples of such environments are Smart Homes, probably the most well-known and well-advertised realization of the concept of Ambient Intelligence. But other applications are feasible and equally relevant e. All these environments can be equipped in such a way that they cooperate to improve safety, comfort and efficiency of the people interacting with them.

This talk will describe the characteristics of these systems, provide examples of applications and highlight the challenges and opportunities ahead for the intended audience of ICAART' He is a member of the LabMag a research lab on multi-agents systems. His current research interests include Creative Artificial Systems, Collective artificial Art, swarm intelligence, swarm robotics, social simulation and multi-agent systems coordination.

Abstract As we can easily imagine it is easy for a group of non-coordinated artificial agents to produce a chaotic artistic pattern. I will discuss the importance of multi-agent coordination in the formation of collective artistic patterns. Artificial Life has been a recent inspiration in the media arts, specially the concepts of self- organization, evolution and behavior based robotics.

Rule- Based Expert Systems: the MYCIN Experiments of the Stanford Heuristic Programming Project

The study of self- organization has revealed that numerous sophisticated pattern formation, decision making and collective behavior are the emergent result of very simple behaviors performed by masses of individuals relying only on local information. I will speak about my experience in designing societies composed by a large number of very simple micro- painters that have very limited perception and communication abilities that try to coordinate and make emerge a collective digital painting.

I will focus on direct and indirect forms of communication for achieving coordination. I will begin describing the estigmergic micro-painters, which are coordinated by the patterns that they are producing. The work they are making, changing the environment, influence the other's activities. I will also also present self-organised direct coordination based on mimetic forms of interaction, where micro-agents can make collective consensual decisions regarding their movement inside the canvas and the selection of color, making emerge aesthetically interesting patterns.

In the talk, after shortly describing the s-bots hardware and the methodology we followed to develop algorithms for their control, I will focus on the capabili- ties of the swarm-bot robotic system by showing video recordings of some of the many experiments we performed to study coordinated movement, path formation, self-assembly, collective transport, shape formation and reconfiguration, distri- buted fault detection and other collective behaviors.

Brief Bio Prof. The unit is a center of excellence appointed by the Academy of Finland. In the center, Honkela is the head of the Computational Cognitive Systems research group.

Rule-based expert systems : the MYCIN experiments of the Stanford Heuristic Programming Project

Earlier he has served as a professor at the laboratory of computer and information science at TKK and as a professor at the Media Lab of University of Art and Design Helsinki. Honkela has approximately one hundred scientific publications. He has conducted research on several areas related to artificial and computational intelligence, cognitive modeling and natural language processing including a central role in the development of the Websom method for visual information retrieval and text mining based on the Kohonen self-organizing map algorithm.

He has been in a responsible position for a large number of scientific conferences and workshops. Abstract It is commonplace to view autonomous agents by considering how much freedom they exhibit in their goal-directed behavior. In other words, the level of motivational autonomy is then in focus. In this presentation, I will discuss, however, why and how the conceptual autonomy of agents is another crucial issue in the field of multiagent system development. In many systems, the agents are provided with a shared conceptual ground.

This poses severe limitations for the autonomy of the agents. Namely, it is a reasonable requirement that autonomous agents should be able to interact with each other robustly in open-ended changing environments. As each agent has its own developmental history and as the environments vary to some extent from agent to agent, it is necessary for each agent to build a model of its environment in an individual manner.

Lecture 8: Rule-Based Expert Systems -1

On the other hand, the agents need to compare these models with each other to enable shared conceptual ground. This can realistically take place through communication in partially shared contexts leading into a sufficient convergence of mapping between the language used by the agents and their individual conceptual systems.

Edward H Shortliffe - Citações do Google Acadêmico

In the presentation, I will also discuss what kind of implications these considerations have for the area of artificial intelligence in general. Brief Bio Dr. Augusto's research experience since has been focused on AI-related problems with emphasis on temporal reasoning. His latest research activities have explored the application of spatio-temporal reasoning to Ambient Intelligence AmI in general and Smart Homes in particular. Abstract Ambient Intelligence is growing fast as a multi-disciplinary area which promises to have a real beneficial influence in our society and to revolutionize the way people interacts with computing.


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The basic idea is that by enriching an environment with technology sensors and devices interconnected through networks , a Smart Environment, systems can be built such that information gathered in real-time and historical data accumulated can be used to support decisions that benefit the users of that environment. An examples of such environments are Smart Homes, probably the most well-known and well-advertised realization of the concept of Ambient Intelligence. But other applications are feasible and equally relevant e.

All these environments can be equipped in such a way that they cooperate to improve safety, comfort and efficiency of the people interacting with them. This talk will describe the characteristics of these systems, provide examples of applications and highlight the challenges and opportunities ahead for the intended audience of ICAART' He is a member of the LabMag a research lab on multi-agents systems.

His current research interests include Creative Artificial Systems, Collective artificial Art, swarm intelligence, swarm robotics, social simulation and multi-agent systems coordination.

Abstract As we can easily imagine it is easy for a group of non-coordinated artificial agents to produce a chaotic artistic pattern. I will discuss the importance of multi-agent coordination in the formation of collective artistic patterns. Artificial Life has been a recent inspiration in the media arts, specially the concepts of self- organization, evolution and behavior based robotics.

The study of self- organization has revealed that numerous sophisticated pattern formation, decision making and collective behavior are the emergent result of very simple behaviors performed by masses of individuals relying only on local information. I will speak about my experience in designing societies composed by a large number of very simple micro- painters that have very limited perception and communication abilities that try to coordinate and make emerge a collective digital painting.

I will focus on direct and indirect forms of communication for achieving coordination. I will begin describing the estigmergic micro-painters, which are coordinated by the patterns that they are producing. The work they are making, changing the environment, influence the other's activities. I will also also present self-organised direct coordination based on mimetic forms of interaction, where micro-agents can make collective consensual decisions regarding their movement inside the canvas and the selection of color, making emerge aesthetically interesting patterns.