'Policy learning' diaporamas de présentation

Reinforcement Learning

Reinforcement Learning. Based on Slides by Avi Pfeffer and David Parkes. Mechanism. Reward. State. Closed Loop Interactions. Environment. Agent. Sensors. Actuators. Percepts. Actions. Reinforcement Learning. When mechanism(=model) is unknown

975 views • 69 slides

PA 395 Day 1 Non-Profits and the Environment Gary Flomenhoft June 6, 2003

PA 395 Day 1 Non-Profits and the Environment Gary Flomenhoft June 6, 2003. Gijs Thieme drives his Zephyr raft under the dumping platform of the Rijnborg just as two barrels of nuclear waste are dropped. (From The Greenpeace Story, Brown and May, 1989). My background.

572 views • 46 slides

Evidence Based Policy Making The Torino Process and ToriNet Belgrade, 6 December 2011

Evidence Based Policy Making The Torino Process and ToriNet Belgrade, 6 December 2011. 1. THE TORINO PROCESS 2012. The Torino Process is a participatory process leading to an evidence-based areview of VET policies in a given country. 2. PURPOSE.

513 views • 40 slides

National Movement for Quality and Productivity Improvement ( Kaizen )

National Movement for Quality and Productivity Improvement ( Kaizen ). Policy Formulation in Developing Countries GRIPS Development Forum. Policy Learning and Private Sector Dynamism. Dynamic Capacity Development requires efforts by both the public and private sectors.

676 views • 39 slides

EU Interregional C ooperation State of play and perspectives Jason Martinez | Project Officer

EU Interregional C ooperation State of play and perspectives Jason Martinez | Project Officer Joint Technical Secretariat RECOMMEND final conference 11 September 2014, Varna. INTERREG IVC state of play. 204 projects. 2 274 partners. 90% of 271 NUTS 2 regions covered.

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Industrial Policy in Africa Learning Mindset and Methods from East Asia

Industrial Policy in Africa Learning Mindset and Methods from East Asia. Kenichi Ohno National Graduate Institute for Policy Studies (GRIPS), Tokyo, October 2010. Topics. Need for concrete and pragmatic learning and instruction Standard policy menu in East Asia

366 views • 23 slides

Reinforcement Learning for 3 vs. 2 Keepaway

Reinforcement Learning for 3 vs. 2 Keepaway. P. Stone, R. S. Sutton, and S. Singh Presented by Brian Light. Robotic Soccer. Sequential decision problem Distributed multi-agent domain Real-time Partially observable Noise Large state space. Reinforcement Learning.

342 views • 23 slides

EU Research Agenda: The European Research Area and Horizon 2020

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Regional Workshop on EVIDENCE BASED POLICY MAKING

Regional Workshop on EVIDENCE BASED POLICY MAKING. Madlen Serban Vienna, 9 November 2009. What is the ETF?. Agency of the European Union Expert advice and support to the Commission and partner countries Specific field: human capital development

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Policy Learning: EU investments in Secondary Education in SEE Knowledge Economy Forum IV

Policy Learning: EU investments in Secondary Education in SEE Knowledge Economy Forum IV Istanbul, 23 March 2005 Arjen Vos. EU Competitiveness Educational attainment Low skills Early school leavers Geographical and professional mobility Investment in human resources and quality

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Monitoring Policy Making: Goals, processes and information demand aris.kaloudis@nifustep.no

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Direct investments as an engine of technological change in Malaysia: The role of networked policy

Direct investments as an engine of technological change in Malaysia: The role of networked policy. Globelics Academy in Lisbon, 02-11 May 2007. A. Motivation. FDI-based development strategy Aim: leveraging foreign technology for local development But: Mixed results .

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THE LISBON STRATEGY AS POLICY CO-ORDINATION Does it promote policy learning?

THE LISBON STRATEGY AS POLICY CO-ORDINATION Does it promote policy learning?. Iain Begg European Institute London School of Economics & Political Science. LISBON FAULT-LINES. Strategic aims not really contested But shifting priorities undermine consistency

246 views • 13 slides

Monte-Carlo Methods

Monte-Carlo Methods. Learning methods averaging complete episodic returns Slides based on [Sutton & Barto : Reinforcement Learning: An Introduction , 1998]. Differences with DP/TD. Differences with DP methods: Real RL: Complete transition model not necessary

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Key Features of EU Policy Processes

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The Internationalisation of Performance Management and Budgeting: Towards an Explanatory Framework

The Internationalisation of Performance Management and Budgeting: Towards an Explanatory Framework. Dr. Richard Common Herbert Simon Institute Manchester Business School University of Manchester, UK. Introduction.

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Tension session I

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Lecture 33 of 42 Fall, 2005 Relational Graphical Models

Lecture 33 of 42 Fall, 2005 Relational Graphical Models. William H. Hsu Friday, 11 November 2005 CIS 490: Introduction to Artificial Intelligence CIS 730: Principles of Artificial Intelligence Kansas State University http://www.kddresearch.org/Courses/Fall-2005/CIS730. Lecture Outline.

157 views • 4 slides