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didattica:magistrale:dcc:ay_2021:main [2020/09/28 15:29]
emanuela [Course Objectives]
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**:
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 D1 - KNOWLEDGE AND UNDERSTANDING D1 - KNOWLEDGE AND UNDERSTANDING
  At the end of the course, the student should know and understand:  At the end of the course, the student should know and understand:
-  ​Ordered List Item+      ​issues relevant to the modelling of a complex system 
 +        - 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 D2 - APPLYING KNOWLEDGE AND UNDERSTANDING
  At the end of the course, the student should be able to:  At the end of the course, the student should be able to:
-  ​Ordered List Item+    ​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 D3 - MAKING JUDGEMENTS
- At the end of the course, the student must be able to: + At the end of the course, the student must be able to select
-    - choose ​the best calculus ​and the more suitable ​modelling ​approach to characterize the structure and the behaviour of a complex system;+    - 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 D4 - COMMUNICATION SKILLS
     - write a short review in LaTex     - write a short review in LaTex
-    - write an essay about the state of the art of an assigned research topic +    - write an essay about the assigned research topic 
-    - make a short presentation ​about the assigned ​research ​topic+    - make a short presentation ​of the assigned topic
  
 D5 - LEARNING SKILLS ​ D5 - LEARNING SKILLS ​
-  ​At the end of the course, the student should be able to: + At the end of the course, the student should be able to: 
-      formally characterize ​the structure and dynamics ​of complex systems. +        autonomously understand if the evolution ​of the model of a given system can be described and coordinated through ​the analysis of its phenomenological data.
-      - analyse ​the agent-base modelling and the multiagent systems approach. +
-      - characterize the evolution ​of a model with the analysis of real 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