Situated Coordination

Similar documents
Agents as Intentional Systems

Artificial Intelligence Lecture 7

Artificial Intelligence CS 6364

Agents and Environments

Web-Mining Agents Cooperating Agents for Information Retrieval

Introduction to Artificial Intelligence 2 nd semester 2016/2017. Chapter 2: Intelligent Agents

Intelligent Autonomous Agents. Ralf Möller, Rainer Marrone Hamburg University of Technology

Module 1. Introduction. Version 1 CSE IIT, Kharagpur

Intelligent Agents. CmpE 540 Principles of Artificial Intelligence

Web-Mining Agents Cooperating Agents for Information Retrieval

Programming with Goals (3)

Artificial Intelligence

Grounding Ontologies in the External World

Princess Nora University Faculty of Computer & Information Systems ARTIFICIAL INTELLIGENCE (CS 370D) Computer Science Department

Multi-agent Engineering. Lecture 4 Concrete Architectures for Intelligent Agents. Belief-Desire-Intention Architecture. Ivan Tanev.

Towards tailored and targeted asthma self-management using mobile technologies

How do you design an intelligent agent?

Foundations of Artificial Intelligence

Agents. Environments Multi-agent systems. January 18th, Agents

DYNAMICISM & ROBOTICS

Deliberating on Ontologies: The Present Situation. Simon Milton Department of Information Systems, The University of Melbourne

Contents. Foundations of Artificial Intelligence. Agents. Rational Agents

Intelligent Agents. Chapter 2

ICS 606. Intelligent Autonomous Agents 1. Intelligent Autonomous Agents ICS 606 / EE 606 Fall Reactive Architectures

Semiotics and Intelligent Control

CS324-Artificial Intelligence

EEL-5840 Elements of {Artificial} Machine Intelligence

Chapter 2: Intelligent Agents

LECTURE 5: REACTIVE AND HYBRID ARCHITECTURES

CS 771 Artificial Intelligence. Intelligent Agents

Intelligent Agents. Philipp Koehn. 16 February 2017

A Computational Framework for Concept Formation for a Situated Design Agent

High-level Vision. Bernd Neumann Slides for the course in WS 2004/05. Faculty of Informatics Hamburg University Germany

Programming Intentional Agents in AgentSpeak(L) and Jason

AVR Based Gesture Vocalizer Using Speech Synthesizer IC

Robot Learning Letter of Intent

Perception Lie Paradox: Mathematically Proved Uncertainty about Humans Perception Similarity

Robotics Summary. Made by: Iskaj Janssen

Transducer/Receiver Function Test Procedure

Perceptual Anchoring with Indefinite Descriptions

Artificial Intelligence

Thrive Hearing Control: An app for a hearing revolution

Intelligent Agents. Instructor: Tsung-Che Chiang

Intelligent Agents. Instructor: Tsung-Che Chiang


Lecture 5- Hybrid Agents 2015/2016

Intelligent Agents. Soleymani. Artificial Intelligence: A Modern Approach, Chapter 2

KECERDASAN BUATAN 3. By Sirait. Hasanuddin Sirait, MT

Assignment Question Paper I

Statistical Analysis and Design Implication for Automatic Depression Detection and Support System

Inferring Actions and Observations from Interactions

AI: Intelligent Agents. Chapter 2

PROJECT PERIODIC REPORT

An Empirical Study of Agent Programs

A wireless medical sensor application and the problems it poses

Personalized HealthCare and Agent Technologies

Ontologies and Reasoning for Ambient Assisted Living

Artificial Intelligence. Intelligent Agents

tado setup overview A compact setup guide on how to install the tado Smart Thermostat and the tado Extension Kit in different heating setups.

Intelligent Medicine Case for Dosing Monitoring and Support

A Multimodal Interface for Robot-Children Interaction in Autism Treatment

How-To Evaluate a Veterinary Digital Radiography System A SPECIAL REPORT

NIH Public Access Author Manuscript Stud Health Technol Inform. Author manuscript; available in PMC 2010 February 28.

AC : USABILITY EVALUATION OF A PROBLEM SOLVING ENVIRONMENT FOR AUTOMATED SYSTEM INTEGRATION EDUCA- TION USING EYE-TRACKING

22c:145 Artificial Intelligence

Intelligent Agents. Chapter 2 ICS 171, Fall 2009

CS148 - Building Intelligent Robots Lecture 5: Autonomus Control Architectures. Instructor: Chad Jenkins (cjenkins)

Medical Planning. David Glasspool. Advanced Computation Laboratory, Cancer Research UK

A PARALLEL MICROSIMULATION PACKAGE FOR MODELLING CANCER SCREENING POLICIES

A brief comparison between the Subsumption Architecture and Motor Schema Theory in light of Autonomous Exploration by Behavior

Unmanned autonomous vehicles in air land and sea

A SITUATED APPROACH TO ANALOGY IN DESIGNING

Artificial Intelligence. Outline

A Telematic System for Diabetes Management, Reporting and Patient Advice

Intelligent Agents. BBM 405 Fundamentals of Artificial Intelligence Pinar Duygulu Hacettepe University. Slides are mostly adapted from AIMA

Function-Behaviour-Structure: A Model for Social Situated Agents

Artificial Intelligence Agents and Environments 1

A MODEL OF DESIGNING THAT INCLUDES ITS SITUATEDNESS

Intelligent Agents. Outline. Agents. Agents and environments

Emergency Monitoring and Prevention (EMERGE)

Dr. Mustafa Jarrar. Chapter 2 Intelligent Agents. Sina Institute, University of Birzeit

CHAPTER 3 RESEARCH METHODOLOGY. In this chapter, research design, data collection, sampling frame and analysis

Improving the Efficiency and Effectiveness of Cognitive Behavioral Therapy: The Utility of a Provider Portal

Operational Analysis of Cognitive Theories for a Ubiquitous Cognitive System

Autonomous Multi-Criteria Decision-Making in Ambient Intelligence

FUTURE SMART ENERGY SOFTWARE HOUSES

Cognitive Maps-Based Student Model

Engaging with the new EU regulatory landscape for medical devices. Challenges and opportunities

Affective Computing for Intelligent Agents. Introduction to Artificial Intelligence CIS 4930, Spring 2005 Guest Speaker: Cindy Bethel

An Evolutionary Approach to the Representation of Adverse Events

CS 331: Artificial Intelligence Intelligent Agents

Biology 20: Module 6 1 Assignment. Module 6 The Motor System and Homeostasis. Student Name:

STIN2103. Knowledge. engineering expert systems. Wan Hussain Wan Ishak. SOC 2079 Ext.: Url:

CS 331: Artificial Intelligence Intelligent Agents

Type-2 fuzzy control of a fed-batch fermentation reactor

Proposal for a Multiagent Architecture for Self-Organizing Systems (MA-SOS)

Recent Developments in Processing of Fats and Oils

The Do s and Don ts of Pressure Transducers

Motivations and Goal-Directed Autonomy

CS343: Artificial Intelligence

Transcription:

Situated Coordination Distributed Systems L-A Sistemi Distribuiti L-A Andrea Omicini & Matteo Casadei andrea.omicini@unibo.it, m.casadei@unibo.it Ingegneria Due Alma Mater Studiorum Università di Bologna a Cesena Academic Year 2008/2009 Omicini & Casadei (Università di Bologna) 9bis Situated Coordination A.Y. 2008/2009 1 / 21

Outline Outline 1 Extending ReSpecT 2 A Case Study Omicini & Casadei (Università di Bologna) 9bis Situated Coordination A.Y. 2008/2009 2 / 21

Outline Extending ReSpecT 1 Extending ReSpecT 2 A Case Study Omicini & Casadei (Università di Bologna) 9bis Situated Coordination A.Y. 2008/2009 3 / 21

Extending ReSpecT Situatedness & Coordination Situatedness... essentially, strict coupling with the environment technically, the ability to properly perceive and react to changes in the environment one of the most critical issues in distributed systems conceptual clash between pro-activeness in process behaviour and reactivity w.r.t. environment change still one of the most critical issues for artificial intelligence & robotics... & coordination essentially, situatedness concerns interaction between processes and the environment technically, situatedness can be conceived as a coordination problem how to handle and govern interaction between pro-active processes and an ever-changing environment Omicini & Casadei (Università di Bologna) 9bis Situated Coordination A.Y. 2008/2009 4 / 21

Extending ReSpecT Goals Overall goal of the research putting coordination models to test in the challenging context of situatedness understanding how classical coordination languages need to be extended to support the coordination of situated processes & distributed systems Omicini & Casadei (Università di Bologna) 9bis Situated Coordination A.Y. 2008/2009 5 / 21

Extending ReSpecT Situating ReSpecT ReSpecT tuple centres for environment engineering Distributed systems are immersed into an environment, and should be reactive to events of any sort Also, coordination media should mediate any activity toward the environment, allowing for a fruitful interaction ReSpecT tuple centres should be able to capture general environment events, and to generally mediate process-environment interaction Situating ReSpecT: extensions In [Casadei and Omicini, 2009], the ReSpecT language has been revised and extended so as to capture environment events, and express general MAS-environment interactions ReSpecT captures, reacts to, and observes general environment events ReSpecT can explicitly interact with the environment Omicini & Casadei (Università di Bologna) 9bis Situated Coordination A.Y. 2008/2009 6 / 21

Extending ReSpecT Extending ReSpecT towards Situatedness I Environment events ReSpecT tuple centres are extended to capture two classes of environmental events the interaction with sensors perceiving environmental properties, through environment predicate get( Key, Value ) the interaction with actuators affecting environmental properties, through environment predicate set( Key, Value ) Source and target of a tuple centre event can be any external resource a suitable identification scheme both at the syntax and at the infrastructure level is introduced for environmental resources Properties of an environmental event can be observed through the observation predicate env( Key, Value ) Omicini & Casadei (Università di Bologna) 9bis Situated Coordination A.Y. 2008/2009 7 / 21

Extending ReSpecT Extending ReSpecT towards Situatedness II Environment communication The ReSpecT language is extended to express explicit communication with environmental resources The body of a ReSpecT reaction can contain a tuple centre predicate of the form EnvResIdentifier? get( Key, Value ) enabling a tuple centre to get properties of environmental resources EnvResIdentifier? set( Key, Value ) enabling a tuple centre to set properties of environmental resources Omicini & Casadei (Università di Bologna) 9bis Situated Coordination A.Y. 2008/2009 8 / 21

Extending ReSpecT Extending ReSpecT towards Situatedness III Transducers Specific environment events have to be translated into well-formed ReSpecT tuple centre events This should be done at the infrastructure level, through a general-purpose schema that could be specialised according to the nature of any specific resource A ReSpecT transducer is a component able to bring environment-generated events to a ReSpecT tuple centre (and back), suitably translated according to the general ReSpecT event model Each transducer is specialised according to the specific portion of the environment it is in charge of handling typically, the specific resource it is aimed at handling, like a temperature sensor, or a heater. Omicini & Casadei (Università di Bologna) 9bis Situated Coordination A.Y. 2008/2009 9 / 21

Outline A Case Study 1 Extending ReSpecT 2 A Case Study Omicini & Casadei (Università di Bologna) 9bis Situated Coordination A.Y. 2008/2009 10 / 21

A Case Study Controlling Environmental Properties of Physical Areas A set of real sensors are used to measure some environmental property (for instance, temperature) within an area where they are located Such information is then exploited to govern suitably placed actuators (say, heaters) that can affect the value of the observed property in the environment Sensors are supposed to be cheap and non-smart, but provided with some kind of communication interface either wireless or wired that makes it possible to send streams of sampled values of the environmental property under observation Accordingly, sensors are active devices, that is, devices pro-actively sending sensed values at a certain rate with no need of being asked for such data this is what typically occurs in pervasive computing scenarios Altogether, actuators and sensors are part of a distributed system aimed at controlling environmental properties (in the case study, temperature), which are affected by actuators based on the values measured by sensors and the designed control policies as well Coordination policies can be suitably automated and encapsulated within environment artifacts controlling sensors and actuators Omicini & Casadei (Università di Bologna) 9bis Situated Coordination A.Y. 2008/2009 11 / 21

A Case Study Case Study: ReSpecT-based Architecture Omicini & Casadei (Università di Bologna) 9bis Situated Coordination A.Y. 2008/2009 12 / 21

A Case Study Case Study: Artifact Structure Artifacts are internally defined in terms of ReSpecT tuple centres: <<sensor>> artifacts wrapping real temperature sensors which perceive temperature of different areas of the room <<actuator>> artifacts wrapping actuators, which act as heating devices so as to control temperature <<aggregator>> artifact provides an aggregated view of the temperature values perceived by sensors spread in the room since it is linked to <<sensor>> artifacts: <<sensor>> artifacts update tuples on <<aggregator>> artifact through linkability Omicini & Casadei (Università di Bologna) 9bis Situated Coordination A.Y. 2008/2009 13 / 21

A Case Study Case Study: Sensor Artifacts %(1) reaction( get(temperature, Temp), from_env, ( event_time(time), event_source(sensor(id)), out(sensed_temperature(id,temp,time)), tc_aggr@node_aggr? out(sensed_temperature(id,temp)) ) ). %(2) reaction( out(sensed_temperature(_,temp,_)), from_tc, ( in(current_temperature(_)), out(current_temperature(temp)) ) ). Behaviour Reaction (1) is triggered by external events generated by a temperature sensor Reaction (2) updates current temperature Omicini & Casadei (Università di Bologna) 9bis Situated Coordination A.Y. 2008/2009 14 / 21

A Case Study Case Study: Aggregator Artifacts %(4) reaction( out(sensed_temperature(id,temp)), from_tc, ( in(total_temperature(oldtotaltemp), in(sensed_temperature(id,oldtemp)), TotalTemp is OldTotalTemp - OldTemp + Temp, out(total_temperature(totaltemp), rd(number_of_sensors(sensorno), AvgTemp is TotalTemp / SensorNo, in(average_temp(_)), out(average_temp(avgtemp)) ) ). Behaviour Reaction (4) keeps track of the current state of the average temperature Omicini & Casadei (Università di Bologna) 9bis Situated Coordination A.Y. 2008/2009 15 / 21

A Case Study Case Study: Agents Observable behaviour Agents are goal-oriented and proactive entities that control temperature of the room 1 get local information from sensor tc sens@node i? rd(current temperature(temp i)) 2 get global information from aggregator tc aggr@node aggr? rd(average temp(avgtemp)) 3 deliberate action by determining TempVar based on Temp i and AvgTemp 4 act upon actuators (if TempVar 0) tc-heat i@node i? out(change temperature(tempvar)) Omicini & Casadei (Università di Bologna) 9bis Situated Coordination A.Y. 2008/2009 16 / 21

A Case Study Case Study: Actuator Artifacts %(3) reaction( out(change_temperature(tempvar)), from_agent, actuator_i? set(temp_inc,tempvar) ). Behaviour When the controller agent deliberate an increment in the temperature a tc-heat i@node i? out(change temperature(tempvar)) reaches the actuator artifact by reaction (3), a suitable signal is sent to the actuator, through the suitably-installed transducer Omicini & Casadei (Università di Bologna) 9bis Situated Coordination A.Y. 2008/2009 17 / 21

Conclusions Conclusion & Future Work Conclusion In this lesson we discussed the role of coordination languages for situatedness extended the ReSpecT coordination language to support situatdness showed a simple case study of a ReSpecT-based pervasive system for controlling environmental properties in physical areas the example was actually built with physical sensors To Do Generalising the abstraction of transducer in ReSpecT Experimenting situated ReSpecT to the modelling and design of other pervasive scenarios Omicini & Casadei (Università di Bologna) 9bis Situated Coordination A.Y. 2008/2009 18 / 21

Conclusions 1 Extending ReSpecT 2 A Case Study Omicini & Casadei (Università di Bologna) 9bis Situated Coordination A.Y. 2008/2009 19 / 21

Bibliography I Conclusions Casadei, M. and Omicini, A. (2009). Situated tuple centres in ReSpecT. In Shin, S. Y., Ossowski, S., Menezes, R., and Viroli, M., editors, 24th Annual ACM Symposium on Applied Computing (SAC 2009), volume III, pages 1361 1368, Honolulu, Hawai i, USA. ACM. Omicini & Casadei (Università di Bologna) 9bis Situated Coordination A.Y. 2008/2009 20 / 21

Conclusions Situated Coordination Distributed Systems L-A Sistemi Distribuiti L-A Andrea Omicini & Matteo Casadei andrea.omicini@unibo.it, m.casadei@unibo.it Ingegneria Due Alma Mater Studiorum Università di Bologna a Cesena Academic Year 2008/2009 Omicini & Casadei (Università di Bologna) 9bis Situated Coordination A.Y. 2008/2009 21 / 21