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Michael P. Wellman
Michael Paul Wellman
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- affiliation: University of Michigan, Ann Arbor, USA
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2020 – today
- 2023
- [c161]Yongzhao Wang, Michael P. Wellman:
Empirical Game-Theoretic Analysis for Mean Field Games. AAMAS 2023: 1025-1033 - [c160]Zun Li, Marc Lanctot, Kevin R. McKee, Luke Marris, Ian Gemp, Daniel Hennes, Kate Larson, Yoram Bachrach, Michael P. Wellman, Paul Muller:
Search-Improved Game-Theoretic Multiagent Reinforcement Learning in General and Negotiation Games. AAMAS 2023: 2445-2447 - [c159]Yongzhao Wang, Michael P. Wellman:
Regularization for Strategy Exploration in Empirical Game-Theoretic Analysis. AAMAS 2023: 2484-2486 - [c158]Yongzhao Wang, Michael P. Wellman:
Game Model Learning for Mean Field Games. AAMAS 2023: 2905-2907 - [i41]Zun Li, Marc Lanctot, Kevin R. McKee, Luke Marris, Ian Gemp, Daniel Hennes, Paul Muller, Kate Larson, Yoram Bachrach, Michael P. Wellman:
Combining Tree-Search, Generative Models, and Nash Bargaining Concepts in Game-Theoretic Reinforcement Learning. CoRR abs/2302.00797 (2023) - [i40]Christine Konicki, Mithun Chakraborty, Michael P. Wellman:
Exploiting Extensive-Form Structure in Empirical Game-Theoretic Analysis. CoRR abs/2302.01366 (2023) - [i39]Yongzhao Wang, Michael P. Wellman:
Regularization for Strategy Exploration in Empirical Game-Theoretic Analysis. CoRR abs/2302.04928 (2023) - [i38]Max Olan Smith, Michael P. Wellman:
Co-Learning Empirical Games and World Models. CoRR abs/2305.14223 (2023) - 2022
- [c157]Yongzhao Wang, Qiurui Ma, Michael P. Wellman:
Evaluating Strategy Exploration in Empirical Game-Theoretic Analysis. AAMAS 2022: 1346-1354 - [c156]Christine Konicki, Mithun Chakraborty, Michael P. Wellman:
Exploiting Extensive-Form Structure in Empirical Game-Theoretic Analysis. WINE 2022: 132-149 - 2021
- [j72]Xintong Wang
, Christopher Hoang, Yevgeniy Vorobeychik
, Michael P. Wellman
:
Spoofing the Limit Order Book: A Strategic Agent-Based Analysis. Games 12(2): 46 (2021) - [c155]Zun Li, Michael P. Wellman:
Evolution Strategies for Approximate Solution of Bayesian Games. AAAI 2021: 5531-5540 - [c154]Katherine Mayo, Michael P. Wellman:
A Strategic Analysis of Portfolio Compression. AAMAS 2021: 1599-1601 - [c153]Katherine Mayo, Michael P. Wellman:
A strategic analysis of portfolio compression. ICAIF 2021: 20:1-20:8 - [c152]Katherine Mayo, Shaily Fozdar, Michael P. Wellman:
An agent-based model of strategic adoption of real-time payments. ICAIF 2021: 45:1-45:9 - [c151]Megan Shearer, David Byrd, Tucker Hybinette Balch, Michael P. Wellman:
Stability effects of arbitrage in exchange traded funds: an agent-based model. ICAIF 2021: 49:1-49:9 - [c150]Max Olan Smith, Thomas Anthony, Michael P. Wellman:
Iterative Empirical Game Solving via Single Policy Best Response. ICLR 2021 - [c149]Yongzhao Wang, Arunesh Sinha
, Sky Ch-Wang, Michael P. Wellman:
Building Action Sets in a Deep Reinforcement Learner. ICMLA 2021: 484-489 - [c148]Xintong Wang, David M. Pennock, Nikhil R. Devanur, David M. Rothschild, Biaoshuai Tao, Michael P. Wellman:
Designing a Combinatorial Financial Options Market. EC 2021: 864-883 - [i37]Feiran Jia, Aditya Mate, Zun Li, Shahin Jabbari, Mithun Chakraborty, Milind Tambe, Michael P. Wellman, Yevgeniy Vorobeychik:
A Game-Theoretic Approach for Hierarchical Policy-Making. CoRR abs/2102.10646 (2021) - [i36]Yongzhao Wang, Qiurui Ma, Michael P. Wellman:
Evaluating Strategy Exploration in Empirical Game-Theoretic Analysis. CoRR abs/2105.10423 (2021) - [i35]Max Olan Smith, Thomas Anthony, Michael P. Wellman:
Iterative Empirical Game Solving via Single Policy Best Response. CoRR abs/2106.01901 (2021) - [i34]Xintong Wang, David M. Pennock, Nikhil R. Devanur, David M. Rothschild, Biaoshuai Tao, Michael P. Wellman:
Designing a Combinatorial Financial Options Market. CoRR abs/2109.06443 (2021) - [i33]Yongzhao Wang, Michael P. Wellman:
Empirical Game-Theoretic Analysis in Mean Field Games. CoRR abs/2112.00900 (2021) - 2020
- [j71]Stefano V. Albrecht
, Peter Stone, Michael P. Wellman
:
Special issue on autonomous agents modelling other agents: Guest editorial. Artif. Intell. 285: 103292 (2020) - [c147]Junyi Li, Xintong Wang, Yaoyang Lin, Arunesh Sinha, Michael P. Wellman:
Generating Realistic Stock Market Order Streams. AAAI 2020: 727-734 - [c146]Zun Li, Michael P. Wellman:
Structure Learning for Approximate Solution of Many-Player Games. AAAI 2020: 2119-2127 - [c145]Xintong Wang, Christopher Hoang, Michael P. Wellman:
Learning-based trading strategies in the face of market manipulation. ICAIF 2020: 25:1-25:8 - [c144]Xintong Wang, Michael P. Wellman:
Market Manipulation: An Adversarial Learning Framework for Detection and Evasion. IJCAI 2020: 4626-4632 - [e7]Sushil Jajodia
, George Cybenko, V. S. Subrahmanian, Vipin Swarup, Cliff Wang, Michael P. Wellman:
Adaptive Autonomous Secure Cyber Systems. Springer 2020, ISBN 978-3-030-33431-4 [contents] - [i32]Junyi Li, Xintong Wang, Yaoyang Lin, Arunesh Sinha, Michael P. Wellman:
Generating Realistic Stock Market Order Streams. CoRR abs/2006.04212 (2020) - [i31]Max Olan Smith, Thomas Anthony, Yongzhao Wang, Michael P. Wellman:
Learning to Play against Any Mixture of Opponents. CoRR abs/2009.14180 (2020)
2010 – 2019
- 2019
- [j70]Iyad Rahwan, Manuel Cebrián, Nick Obradovich
, Josh C. Bongard, Jean-François Bonnefon, Cynthia Breazeal, Jacob W. Crandall, Nicholas A. Christakis, Iain D. Couzin, Matthew O. Jackson
, Nicholas R. Jennings
, Ece Kamar, Isabel M. Kloumann, Hugo Larochelle, David Lazer, Richard McElreath, Alan Mislove, David C. Parkes, Alex 'Sandy' Pentland, Margaret E. Roberts, Azim Shariff, Joshua B. Tenenbaum, Michael P. Wellman
:
Machine behaviour. Nat. 568(7753): 477-486 (2019) - [c143]Thanh Hong Nguyen, Yongzhao Wang, Arunesh Sinha, Michael P. Wellman:
Deception in Finitely Repeated Security Games. AAAI 2019: 2133-2140 - [c142]Arunesh Sinha, Michael P. Wellman:
Incentivizing Collaboration in a Competition. AAMAS 2019: 556-564 - [c141]Mason Wright, Yongzhao Wang, Michael P. Wellman
:
Iterated Deep Reinforcement Learning in Games: History-Aware Training for Improved Stability. EC 2019: 617-636 - [c140]Frank Cheng, Yagil Engel, Michael P. Wellman
:
Cap-and-Trade Emissions Regulation: A Strategic Analysis. IJCAI 2019: 187-193 - [p3]George Cybenko, Michael P. Wellman
, Peng Liu, Minghui Zhu:
Overview of Control and Game Theory in Adaptive Cyber Defenses. Adversarial and Uncertain Reasoning for Adaptive Cyber Defense 2019: 1-11 - [p2]Hamidreza Tavafoghi, Yi Ouyang, Demosthenis Teneketzis, Michael P. Wellman
:
Game Theoretic Approaches to Cyber Security: Challenges, Results, and Open Problems. Adversarial and Uncertain Reasoning for Adaptive Cyber Defense 2019: 29-53 - [p1]Michael P. Wellman
, Thanh Hong Nguyen, Mason Wright:
Empirical Game-Theoretic Methods for Adaptive Cyber-Defense. Adversarial and Uncertain Reasoning for Adaptive Cyber Defense 2019: 112-128 - [e6]Sushil Jajodia, George Cybenko, Peng Liu, Cliff Wang, Michael P. Wellman:
Adversarial and Uncertain Reasoning for Adaptive Cyber Defense - Control- and Game-Theoretic Approaches to Cyber Security. Lecture Notes in Computer Science 11830, Springer 2019, ISBN 978-3-030-30718-9 [contents] - 2018
- [j69]Thanh Hai Nguyen
, Mason Wright, Michael P. Wellman
, Satinder Singh:
Multistage Attack Graph Security Games: Heuristic Strategies, with Empirical Game-Theoretic Analysis. Secur. Commun. Networks 2018: 2864873:1-2864873:28 (2018) - [c139]Thanh Hong Nguyen, Michael P. Wellman, Arunesh Sinha:
Deceitful Attacks in Security Games. AAAI Workshops 2018: 260-267 - [c138]Mason Wright, Michael P. Wellman:
Evaluating the Stability of Non-Adaptive Trading in Continuous Double Auctions: A Reinforcement Learning Approach. AAAI Workshops 2018: 317-324 - [c137]Bryce Wiedenbeck, Fengjun Yang, Michael P. Wellman:
A Regression Approach for Modeling Games With Many Symmetric Players. AAAI 2018: 1266-1273 - [c136]Mason Wright, Michael P. Wellman:
Evaluating the Stability of Non-Adaptive Trading in Continuous Double Auctions. AAMAS 2018: 614-622 - [c135]Nicolas Papernot, Patrick D. McDaniel, Arunesh Sinha
, Michael P. Wellman
:
SoK: Security and Privacy in Machine Learning. EuroS&P 2018: 399-414 - [c134]Megan Shearer, Michael P. Wellman:
Incentivizing Rider Time-Shift in a Multi-Leg Public Transportation System. ATT@IJCAI 2018: 86-93 - [c133]Xintong Wang, Yevgeniy Vorobeychik, Michael P. Wellman
:
A Cloaking Mechanism to Mitigate Market Manipulation. IJCAI 2018: 541-547 - 2017
- [j68]Michael P. Wellman
, Eric Sodomka
, Amy Greenwald:
Self-confirming price-prediction strategies for simultaneous one-shot auctions. Games Econ. Behav. 102: 339-372 (2017) - [j67]Elaine Wah, Mason Wright, Michael P. Wellman
:
Welfare Effects of Market Making in Continuous Double Auctions. J. Artif. Intell. Res. 59: 613-650 (2017) - [j66]Michael P. Wellman
, Uday Rajan:
Ethical Issues for Autonomous Trading Agents. Minds Mach. 27(4): 609-624 (2017) - [c132]Thanh Hong Nguyen, Michael P. Wellman, Satinder Singh:
A Stackelberg Game Model for Botnet Traffic Exfiltration. AAAI Workshops 2017 - [c131]Xintong Wang, Michael Paul Wellman:
Spoofing the Limit Order Book: An Agent-Based Model. AAAI Workshops 2017 - [c130]Xintong Wang, Michael P. Wellman:
Spoofing the Limit Order Book: An Agent-Based Model. AAMAS 2017: 651-659 - [c129]Thanh Hai Nguyen, Mason Wright, Michael P. Wellman
, Satinder Singh:
Multi-Stage Attack Graph Security Games: Heuristic Strategies, with Empirical Game-Theoretic Analysis. MTD@CCS 2017: 87-97 - [c128]Thanh Hai Nguyen, Michael P. Wellman
, Satinder Singh:
A Stackelberg Game Model for Botnet Data Exfiltration. GameSec 2017: 151-170 - [c127]Frank Cheng, Michael P. Wellman
:
Accounting for Strategic Response in an Agent-Based Model of Financial Regulation. EC 2017: 187-203 - [c126]Erik Brinkman, Michael P. Wellman
:
Empirical Mechanism Design for Optimizing Clearing Interval in Frequent Call Markets. EC 2017: 205-221 - 2016
- [j65]Virginia Dignum
, Nigel Gilbert, Michael P. Wellman
:
Introduction to the special issue on autonomous agents for agent-based modeling. Auton. Agents Multi Agent Syst. 30(6): 1021-1022 (2016) - [j64]Michael P. Wellman
:
Putting the agent in agent-based modeling. Auton. Agents Multi Agent Syst. 30(6): 1175-1189 (2016) - [j63]Elaine Wah, Michael P. Wellman
:
Latency arbitrage in fragmented markets: A strategic agent-based analysis. Algorithmic Finance 5(3-4): 69-93 (2016) - [j62]Elaine Wah, Dylan Hurd, Michael P. Wellman
:
Strategic Market Choice: Frequent Call Markets vs. Continuous Double Auctions for Fast and Slow Traders. EAI Endorsed Trans. Serious Games 3(10): e1 (2016) - [c125]Mason Wright, Sridhar Venkatesan, Massimiliano Albanese
, Michael P. Wellman
:
Moving Target Defense against DDoS Attacks: An Empirical Game-Theoretic Analysis. MTD@CCS 2016: 93-104 - [c124]Elaine Wah, Mason Wright, Michael P. Wellman:
Welfare Effects of Market Making in Continuous Double Auctions: Extended Abstract. IJCAI 2016: 4218-4222 - [c123]Frank Cheng, Junming Liu, Kareem Amin, Michael P. Wellman
:
Strategic Payment Routing in Financial Credit Networks. EC 2016: 721-738 - [c122]Kareem Amin, Michael P. Wellman, Satinder Singh:
Gradient Methods for Stackelberg Games. UAI 2016 - [e5]Dale Schuurmans, Michael P. Wellman:
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, February 12-17, 2016, Phoenix, Arizona, USA. AAAI Press 2016, ISBN 978-1-57735-760-5 [contents] - [i30]Nicolas Papernot, Patrick D. McDaniel, Arunesh Sinha, Michael P. Wellman:
Towards the Science of Security and Privacy in Machine Learning. CoRR abs/1611.03814 (2016) - 2015
- [j61]Pranav Dandekar, Ashish Goel, Michael P. Wellman
, Bryce Wiedenbeck:
Strategic Formation of Credit Networks. ACM Trans. Internet Techn. 15(1): 3:1-3:41 (2015) - [c121]Elaine Wah, Michael P. Wellman:
Welfare Effects of Market Making in Continuous Double Auctions. AAMAS 2015: 57-66 - [c120]Bryce Wiedenbeck, Michael P. Wellman:
Learning Payoffs in Large Symmetric Games. AAMAS 2015: 1881-1882 - [c119]Achintya Prakash, Michael P. Wellman
:
Empirical Game-Theoretic Analysis for Moving Target Defense. MTD@CCS 2015: 57-65 - 2014
- [c118]Erik Brinkman, Michael P. Wellman, Scott E. Page:
Signal structure and strategic information acquisition: deliberative auctions with interdependent values. AAMAS 2014: 229-236 - [c117]Bryce Wiedenbeck, Ben-Alexander Cassell, Michael P. Wellman:
Bootstrap statistics for empirical games. AAMAS 2014: 597-604 - [c116]Michael P. Wellman, Achintya Prakash:
Empirical Game-Theoretic Analysis of an Adaptive Cyber-Defense Scenario (Preliminary Report). GameSec 2014: 43-58 - [c115]George Cybenko, Sushil Jajodia, Michael P. Wellman, Peng Liu:
Adversarial and Uncertain Reasoning for Adaptive Cyber Defense: Building the Scientific Foundation. ICISS 2014: 1-8 - [c114]Travis Martin, Grant Schoenebeck
, Michael P. Wellman
:
Characterizing strategic cascades on networks. EC 2014: 113-130 - [c113]Ben-Alexander Cassell, Michael P. Wellman
:
Database Modeling of Empirical Games. DSMM 2014: 6:1-6:6 - [i29]Yagil Engel, Michael P. Wellman:
Multiattribute Auctions Based on Generalized Additive Independence. CoRR abs/1401.3844 (2014) - 2013
- [c112]Brandon A. Mayer, Eric Sodomka, Amy Greenwald, Michael P. Wellman:
Accounting for Price Dependencies in Simultaneous Sealed-Bid Auctions. AAAI Workshop: Trading Agent Design and Analysis 2013 - [c111]Brandon A. Mayer, Eric Sodomka, Amy Greenwald, Michael P. Wellman:
Accounting for price dependencies in simultaneous sealed-bid auctions. EC 2013: 679-696 - [c110]Elaine Wah, Michael P. Wellman:
Latency arbitrage, market fragmentation, and efficiency: a two-market model. EC 2013: 855-872 - [i28]David M. Pennock, Michael P. Wellman:
Compact Securities Markets for Pareto Optimal Reallocation of Risk. CoRR abs/1301.3886 (2013) - [i27]David V. Pynadath, Michael P. Wellman:
Probabilistic State-Dependent Grammars for Plan Recognition. CoRR abs/1301.3888 (2013) - [i26]David M. Pennock, Michael P. Wellman:
Graphical Representations of Consensus Belief. CoRR abs/1301.6732 (2013) - [i25]Chao-Lin Liu, Michael P. Wellman:
Incremental Tradeoff Resolution in Qualitative Probabilistic Networks. CoRR abs/1301.7395 (2013) - [i24]Chao-Lin Liu, Michael P. Wellman:
Using Qualitative Relationships for Bounding Probability Distributions. CoRR abs/1301.7396 (2013) - [i23]David M. Pennock, Michael P. Wellman:
Representing Aggregate Belief through the Competitive Equilibrium of a Securities Market. CoRR abs/1302.1564 (2013) - [i22]David M. Pennock, Michael P. Wellman:
Toward a Market Model for Bayesian Inference. CoRR abs/1302.3593 (2013) - [i21]Peter R. Wurman, Michael P. Wellman:
Optimal Factory Scheduling using Stochastic Dominance A*. CoRR abs/1302.3611 (2013) - [i20]David V. Pynadath, Michael P. Wellman:
Accounting for Context in Plan Recognition, with Application to Traffic Monitoring. CoRR abs/1302.4980 (2013) - [i19]Michael P. Wellman, Matthew Ford, Kenneth Larson:
Path Planning under Time-Dependent Uncertainty. CoRR abs/1302.4987 (2013) - [i18]Marcus J. Huber, Edmund H. Durfee, Michael P. Wellman:
The Automated Mapping of Plans for Plan Recognition. CoRR abs/1302.6821 (2013) - [i17]Michael P. Wellman, Chao-Lin Liu:
State-space Abstraction for Anytime Evaluation of Probabilistic Networks. CoRR abs/1302.6850 (2013) - [i16]Michael P. Wellman:
Exploiting Functional Dependencies in Qualitative Probabilistic Reasoning. CoRR abs/1304.1081 (2013) - [i15]Michael P. Wellman, David Heckerman:
The Role of Calculi in Uncertain Inference Systems. CoRR abs/1304.2747 (2013) - [i14]Michael P. Wellman:
Qualitative Probabilistic Networks for Planning Under Uncertainty. CoRR abs/1304.3115 (2013) - [i13]Bruce D'Ambrosio, Didier Dubois, Philippe Smets, Michael P. Wellman:
Proceedings of the Eighth Conference on Uncertainty in Artificial Intelligence (1992). CoRR abs/1304.3852 (2013) - [i12]Michael P. Wellman, Tae Hyung Kim, Quang Duong:
Analyzing Incentives for Protocol Compliance in Complex Domains: A Case Study of Introduction-Based Routing. CoRR abs/1306.0388 (2013) - [i11]Travis Martin, Grant Schoenebeck, Michael P. Wellman:
Characterizing Strategic Cascades on Networks. CoRR abs/1310.2561 (2013) - 2012
- [j60]Yevgeniy Vorobeychik
, Daniel M. Reeves, Michael P. Wellman
:
Constrained automated mechanism design for infinite games of incomplete information. Auton. Agents Multi Agent Syst. 25(2): 313-351 (2012) - [j59]Ben-Alexander Cassell, Michael P. Wellman
:
Asset pricing under ambiguous information: an empirical game-theoretic analysis. Comput. Math. Organ. Theory 18(4): 445-462 (2012) - [c109]Quang Duong, Michael P. Wellman, Satinder Singh, Michael J. Kearns:
Learning and predicting dynamic networked behavior with graphical multiagent models. AAMAS 2012: 441-448 - [c108]Bryce Wiedenbeck, Michael P. Wellman:
Scaling simulation-based game analysis through deviation-preserving reduction. AAMAS 2012: 931-938 - [c107]Michael P. Wellman
, Bryce Wiedenbeck:
An empirical game-theoretic analysis of credit network formation. Allerton Conference 2012: 386-393 - [c106]Ben-Alexander Cassell, Michael P. Wellman
:
EGTAOnline: An Experiment Manager for Simulation-Based Game Studies. MABS 2012: 85-100 - [c105]Michael P. Wellman, Eric Sodomka, Amy Greenwald:
Self-Confirming Price Prediction Strategies for Simultaneous One-Shot Auctions. UAI 2012: 893-902 - [c104]Pranav Dandekar, Ashish Goel, Michael P. Wellman
, Bryce Wiedenbeck:
Strategic formation of credit networks. WWW 2012: 559-568 - [i10]Michael P. Wellman, Lu Hong, Scott E. Page:
The Structure of Signals: Causal Interdependence Models for Games of Incomplete Information. CoRR abs/1202.3768 (2012) - [i9]Quang Duong, Michael P. Wellman, Satinder Singh:
Knowledge Combination in Graphical Multiagent Model. CoRR abs/1206.3248 (2012) - [i8]Yevgeniy Vorobeychik, Daniel M. Reeves, Michael P. Wellman:
Constrained Automated Mechanism Design for Infinite Games of Incomplete Information. CoRR abs/1206.5288 (2012) - [i7]Anna Osepayshvili, Michael P. Wellman, Daniel M. Reeves, Jeffrey K. MacKie-Mason:
Self-Confirming Price Prediction for Bidding in Simultaneous Ascending Auctions. CoRR abs/1207.1400 (2012) - [i6]Daniel M. Reeves, Michael P. Wellman:
Computing Best-Response Strategies in Infinite Games of Incomplete Information. CoRR abs/1207.4171 (2012) - [i5]Michael P. Wellman, Eric Sodomka, Amy Greenwald:
Self-Confirming Price Prediction Strategies for Simultaneous One-Shot Auctions. CoRR abs/1210.4915 (2012) - 2011
- [b3]Michael P. Wellman
:
Trading Agents. Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan & Claypool Publishers 2011 - [c103]Quang Duong, Michael P. Wellman
, Satinder Singh:
Modeling Information Diffusion in Networks with Unobserved Links. SocialCom/PASSAT 2011: 362-369 - [c102]Ben-Alexander Cassell, Michael P. Wellman:
Agent-based analysis of asset pricing under ambiguous information. SpringSim (ADS) 2011: 21-28 - [c101]Gregory Frazier, Quang Duong, Michael P. Wellman
, Edward Petersen:
Incentivizing Responsible Networking via Introduction-Based Routing. TRUST 2011: 277-293 - [c100]Michael P. Wellman, Lu Hong, Scott E. Page:
The Structure of Signals: Causal Interdependence Models for Games of Incomplete Information. UAI 2011: 727-735 - [i4]William E. Walsh, Michael P. Wellman:
Decentralized Supply Chain Formation: A Market Protocol and Competitive Equilibrium Analysis. CoRR abs/1107.0021 (2011) - [i3]Kevin M. Lochner, Daniel M. Reeves, Yevgeniy Vorobeychik, Michael P. Wellman:
Price Prediction in a Trading Agent Competition. CoRR abs/1107.0034 (2011) - 2010
- [j58]Clint R. Bidlack, Michael P. Wellman:
Exceptional Data Quality using Intelligent Matching and Retrieval. AI Mag. 31(1): 65-73 (2010) - [j57]