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didattica:magistrale:dcc:ay_2021:main [2020/09/28 14:25] emanuela [General Info] |
didattica:magistrale:dcc:ay_2021:main [2020/09/29 10:18] (current) emanuela [Course Objectives] |
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| **ESSE3 Link** | **ESSE3 Link** | ||
| - | * [[https://didattica.unicam.it/Guide/PaginaADErogata.do?ad_er_id=2018*N0*N0*S1*14565*7555&ANNO_ACCADEMICO=2018&mostra_percorsi=S|Distributed Calculus and Coordination - AY 2018/2019]] | + | * [[https://didattica.unicam.it/Guide/PaginaADErogata.do?ad_er_id=2020*N0*N0*S1*15660*7555&ANNO_ACCADEMICO=2020&mostra_percorsi=S|Distributed Calculus and Coordination - AY 2020/2021]] |
| **Lessons schedule**: | **Lessons schedule**: | ||
| * Tuesday, 9am - 11pm (Room, LB1) | * Tuesday, 9am - 11pm (Room, LB1) | ||
| - | * Thursday, 9am - 11pm (Room, Lb1) | + | * Thursday, 9am - 11pm (Room, LB1) |
| **Students Office hours**: | **Students Office hours**: | ||
| - | * Thursday 11pm - 13pm, Palazzo Battibocca - 2nd Piano - Room n.CS-05 | + | * Thursday 11pm - 13pm, Polo Informatico - new building |
| </WRAP> | </WRAP> | ||
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| <WRAP box round 95% center> | <WRAP box round 95% center> | ||
| - | - Be able to characterize the modelling of complex systems. | + | D1 - KNOWLEDGE AND UNDERSTANDING |
| - | - Be able to apply methods, languages and techniques of the distributed calculus and coordination in modelling complex systems. | + | At the end of the course, the student should know and understand: |
| - | - Be able to design a multiagent system using prototyping environment. | + | - issues relevant to the modelling of a complex system |
| - | - Be able to characterize the evolution of a model with the analysis of real phenomenological data. | + | - the concept of entanglement between structure and behaviour |
| + | - issues related to the dynamics of a complex system | ||
| + | - the role of entropy for detecting the state of a complex system | ||
| + | - the concept of emerging behaviour | ||
| + | - the differences among models and languages | ||
| + | - the three formal aspects of a complex system: computation, coordination and adaptation | ||
| + | - the automata-based modelling and forma languages (FSMs) | ||
| + | - the process-based modelling and algebraic languages (CCS) | ||
| + | - the agent-based modelling and coordination languages (Klaim, Linda) | ||
| + | |||
| + | D2 - APPLYING KNOWLEDGE AND UNDERSTANDING | ||
| + | At the end of the course, the student should be able to: | ||
| + | - characterise the structure and dynamics of complex systems | ||
| + | - distinguish interactions from relations, so as communication from coordination | ||
| + | - correlate the behavioural and structural components of a complex system | ||
| + | - analyse whether to apply an agent-base model to a real context | ||
| + | |||
| + | D3 - MAKING JUDGEMENTS | ||
| + | At the end of the course, the student must be able to select: | ||
| + | - the best calculus to characterize the structure of a complex system | ||
| + | - the more suitable approach to model the behaviour of a complex system; | ||
| + | |||
| + | D4 - COMMUNICATION SKILLS | ||
| + | - write a short review in LaTex | ||
| + | - write an essay about the assigned research topic | ||
| + | - make a short presentation of the assigned topic | ||
| + | |||
| + | D5 - LEARNING SKILLS | ||
| + | At the end of the course, the student should be able to: | ||
| + | - autonomously understand if the evolution of the model of a given system can be described and coordinated through the analysis of its phenomenological data. | ||
| </WRAP> | </WRAP> | ||
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| - Models and languages for distributed Calculus: process algebraic calculi, rule-based (CHAM), membrane-based (P-Systems). | - Models and languages for distributed Calculus: process algebraic calculi, rule-based (CHAM), membrane-based (P-Systems). | ||
| - Coordination models and languages: Linda, Klaim | - Coordination models and languages: Linda, Klaim | ||
| - | - Concurrent Programming paradigms: Agent-oriented, Actor-based. | + | - Concurrent Programming paradigms: Agent-oriented |
| - Multiagent modelling and simulation environments: REPAST | - Multiagent modelling and simulation environments: REPAST | ||
| - | - Topological data analysis for driven modelling: S[B] | + | - Topology driven modelling: S[B] |
| </WRAP> | </WRAP> | ||
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| ===== Exams ===== | ===== Exams ===== | ||
| <WRAP box round center 95%> | <WRAP box round center 95%> | ||
| - | **Exam Dates A.Y. 2015/2016** | + | **Exam Dates A.Y. 2020/2021** |
| - | * Winter session dates here | + | * Winter session dates here in [[https://didattica.unicam.it/auth/docente/CalendarioEsami/ElencoAppelliCalEsa.do|ESSE 3]] |
| - | * Summer session dates here | + | * Summer session dates |
| - | * Autumn session dates here | + | * Autumn session dates |
| - | * Winter session dates here (2016) | + | * Winter session dates (2021) |
| **Exam rules**: | **Exam rules**: | ||
| * Homeworks | * Homeworks | ||
