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Agent based simulation and electricity market

Politecnico di Torino - Ceris – Hermes - AEIT Electricity market performance under physical constraints. Agent based simulation and electricity market Pietro TERNA, Department of Economic and Financial Science, University of Torino terna@econ.unito.it , http://web.econ.unito.it/terna.

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Agent based simulation and electricity market

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  1. Politecnico di Torino - Ceris – Hermes - AEIT Electricity market performance under physical constraints • Agent based simulation and electricity market • Pietro TERNA, Department of Economic and Financial Science, • University of Torino • terna@econ.unito.it, http://web.econ.unito.it/terna Real Collegio Carlo Alberto

  2. _______________________________________ Building models: three ways _______________________________________ Real Collegio Carlo Alberto

  3. Three different symbol systems: • verbal argumentations • mathematics • computer simulation(agent based) Real Collegio Carlo Alberto

  4. _______________________________________ How to use agents in simulation models: a radical view _______________________________________ Real Collegio Carlo Alberto

  5. The radical characterization of an ABM must be found into the possibility of real – direct or indirect (via the environment) – interaction amid the agents … avoiding simplifications coming from the use aggregate (simultaneous) equations (going back to the Walrasian auctioneer) Real Collegio Carlo Alberto

  6. _______________________________________ Agent based simulation and real world representation _______________________________________ Real Collegio Carlo Alberto

  7. Social simulation as a computer based way to execute complex mental experiments, but also as a via to represent the complexity of real world simulation = agent-based models Real Collegio Carlo Alberto

  8. _______________________________________ A dictionary _______________________________________ Real Collegio Carlo Alberto

  9. A dictionary, from Conte R, Edmonds B, Moss S., Sawyer R.K., Sociology and Social Theory in Agent Based Social Simulation: A Symposium Computational & Mathematical Organization Theory 7, 183-205,2001 • “1. The purpose of Agent Based Social Simulation (ABSS) is to analyse the properties of social systems defined by dense patterns of interaction among autonomous, cognitive • individuals. • 2. The same modelling techniques that are intended to represent real social systems can also represent software systems such as the Internet and large federated data bases populated by intelligent information agents or, indeed, any other large, complex multi agent system. Multi agent based simulations (MABS) of such systems share the techniques of ABSS.” • My note: • we use frequently the name of Agent Based Model (ABM) or Agent Computational Ecomics (ACE) instead of ABSS; • in computer science the attention is devoted to Multi Agent Systems, MAS; adding “simulation” we have MABS and, in some way, ABSS. Real Collegio Carlo Alberto

  10. _______________________________________ A general structure for agent-based simulation models, the ERA scheme _______________________________________ Real Collegio Carlo Alberto

  11. ERA, Environment, Rules, Agents NN CS GA Avatar http://web.econ.unito.it/terna/ct-era/ct-era.html Real Collegio Carlo Alberto

  12. _______________________________________ Tools _______________________________________ Real Collegio Carlo Alberto

  13. Swarm, http://www.swarm.org SLAPP, Swarm-Like Agent Protocol in Python, temporary at http://eco83.econ.unito.it/terna/slapp ; Python at www.python.org JAS, http://jaslibrary.sourceforge.net/ Ascape, http://www.brook.edu/dynamics/models/ascape/ Repast, http://repast.sourceforge.net/ StarLogo, http://education.mit.edu/starlogo/ StarLogo TNG, http://education.mit.edu/starlogo-tng/ NetLogo, http://ccl.northwestern.edu/netlogo/ SDML (based upon SmallTalk, as a declarative programming tool): http://www.cpm.mmu.ac.uk/sdml/ See also ABLE, http://www.research.ibm.com/able/ JADE,http://jade.tilab.com/ or DAML, www.daml.org didactical perspective nearly videogames Real Collegio Carlo Alberto

  14. We have also specialized agent based simulators, like jES and jESOF http://web.econ.unito.it/terna/jes/ a simulator useful to reproduce enterprises behavior Real Collegio Carlo Alberto

  15. _______________________________________ The surprising world of the Chameleons, with SLAPP From an idea of Marco Lamieri, a project work with Riccardo Taormina _______________________________________ Real Collegio Carlo Alberto

  16. The reinforcement learning algorithm A direct tool: the reinforcement learning. We have a set of states S, related to an environment; a set of possible actions A; a set of scalar rewards, in R. At any time t we have an agent in a state st of S and we can chose the action a in A(st). After the action it will be in st+1 with a reward rt+1. Reward are summed over time with a discount rate factor. Our agent develops the capability of mapping all the possible actions A in a state S to all the related rewards. Real Collegio Carlo Alberto

  17. The metaphorical models we use here is that of the changing color chameleons We have chameleons of three colors: red, green and blue When two chameleons of different colors meet, they both change their color, assuming the third one (If all chameleons get the same color, we have a steady state situation) The metaphor is interpreted in the following way: an agent diffusing innovation or ideas (or political ideas) can change itself via the interaction with other agents: as an example think about an academic scholar working in a completely isolated context or interacting with other scholars or with private entrepreneurs to apply the results of her work Real Collegio Carlo Alberto

  18. A simple rule for a complex environment Let play Real Collegio Carlo Alberto

  19. Running or chasing for identity! • Reinforcement learning and pattern recognition, with bounded rationality • Agent brain built upon 9 Artificial Neural Networks Real Collegio Carlo Alberto

  20. _______________________________________ The surprising world of the Chameleons, with NetLogo _______________________________________ Real Collegio Carlo Alberto

  21. Real Collegio Carlo Alberto

  22. _______________________________________ Electricity market _______________________________________ Real Collegio Carlo Alberto

  23. Leigh Tesfatsion work Real Collegio Carlo Alberto

  24. Leigh Tesfatsion work Real Collegio Carlo Alberto

  25. Leigh Tesfatsion work Real Collegio Carlo Alberto

  26. Leigh Tesfatsion work Real Collegio Carlo Alberto

  27. Leigh Tesfatsion work Real Collegio Carlo Alberto

  28. Leigh Tesfatsion work Real Collegio Carlo Alberto

  29. Leigh Tesfatsion work Real Collegio Carlo Alberto

  30. Leigh Tesfatsion work Real Collegio Carlo Alberto

  31. _______________________________________ From spin glasses to videogames: representing our worlds and their complexity via the use of simple simulation tools, with agents _______________________________________ Real Collegio Carlo Alberto

  32. _______________________________________ Scratch http://weblogs.media.mit.edu/llk/scratch/ _______________________________________ Real Collegio Carlo Alberto

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  34. The credit multiplier (money_supply.sb) Real Collegio Carlo Alberto

  35. _______________________________________ StarLogo TNG http://education.mit.edu/starlogo/ _______________________________________ Real Collegio Carlo Alberto

  36. StarLogo TNG Real Collegio Carlo Alberto

  37. Sperimentiamo la complessità con StarLogo TNG termites2 Real Collegio Carlo Alberto

  38. Sperimentiamo la complessità con StarLogo TNG Fish and Plankton Real Collegio Carlo Alberto

  39. _______________________________________ Squeak http://www.squeak.org/ _______________________________________ Real Collegio Carlo Alberto

  40. Real Collegio Carlo Alberto

  41. _______________________________________ Second Life http://secondlife.com/ _______________________________________ Real Collegio Carlo Alberto

  42. Real Collegio Carlo Alberto

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