Demo Data from SIGIR 2026 / reviewers in the wild / expert
Janusz Marecki
dblp:90/404
· DBLP profile ↗
7ranked-venue papers
2as first author
0since 2021 · last 2013
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 7 · 2 first-authorGraphics, computer vision, multimedia, augmented reality and games · 4 · 2 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Artificial intelligence
2 papers |
Planning, search and constraint satisfaction · 78% Reinforcement learning · 22% | |
| Theoretical computer science
1 paper |
Algorithmic game theory and mechanism design · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
Learning and educational technologies · 100% |
Topics — the 8 heaviest of 10, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Knowledge, reasoning and agents › Planning, search and constraint satisfaction
planning under uncertainty |
0.1 | 1 | 2008 | Towards Faster Planning with Continuous Resources in Stochastic Domains · AAAI 2008 |
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › planning under uncertainty
probabilistic planning |
0.1 | 1 | 2008 | Towards Faster Planning with Continuous Resources in Stochastic Domains · AAAI 2008 |
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › planning › constraint-based planning
resource-constrained planning |
0.1 | 1 | 2008 | Towards Faster Planning with Continuous Resources in Stochastic Domains · AAAI 2008 |
Algorithmic game theory and mechanism design › stackelberg game
bayesian stackelberg game |
0.1 | 1 | 2008 | Efficient Algorithms to Solve Bayesian Stackelberg Games for Security Applications · AAAI 2008 |
Algorithmic game theory and mechanism design
security games |
0.1 | 1 | 2008 | Efficient Algorithms to Solve Bayesian Stackelberg Games for Security Applications · AAAI 2008 |
Algorithmic game theory and mechanism design
stackelberg game |
0.1 | 1 | 2008 | Efficient Algorithms to Solve Bayesian Stackelberg Games for Security Applications · AAAI 2008 |
Machine learning › Reinforcement learning
markov decision process |
0.1 | 1 | 2007 | A Fast Analytical Algorithm for Solving Markov Decision Processes with Real-Valued Resources · IJCAI 2007 |
Learning and educational technologies › educational software
training systems |
0.1 | 1 | 2005 | The DEFACTO System: Training Tool for Incident Commanders · AAAI 2005 |
Methods — techniques the papers use, named apart from their topics
mixed integer linear programming · 0.1analytical algorithm · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2013 | Solution Methods for Constrained Markov Decision Process with Continuous Probability Modulation
Marek Petrik, Dharmashankar Subramanian, Janusz Marecki |
UAI | 3 |
| 2010 | ALARMS: Alerting and Reasoning Management System for Next Generation Aircraft Hazards
Alan Carlin, Nathan Schurr, Janusz Marecki |
UAI | 3 |
| 2010 | Introducing communication in Dis-POMDPs with locality of interactionabstractThe Networked Distributed POMDPs (ND-POMDPs) can model multiagent systems in uncertain domains and have begun to scale-up the number of agents. However, prior work in ND-POMDPs has failed to address communication. Without communication, the size of a Makoto Tasaki, Yuichi Yabu, Yuki Iwanari, Makoto Yokoo, Janusz Marecki, Pradeep Varakantham, Milind Tambe |
Web Intell. Agent Syst. | 5 |
| 2008 | Towards Faster Planning with Continuous Resources in Stochastic Domains
Janusz Marecki, Milind Tambe |
AAAI | 1 |
| 2008 | Efficient Algorithms to Solve Bayesian Stackelberg Games for Security Applications
Praveen Paruchuri, Jonathan P. Pearce, Janusz Marecki, Milind Tambe, Fernando Ordóñez, Sarit Kraus |
AAAI | 3 |
| 2007 | A Fast Analytical Algorithm for Solving Markov Decision Processes with Real-Valued Resources
Janusz Marecki, Sven Koenig, Milind Tambe |
IJCAI | 1 |
| 2005 | The DEFACTO System: Training Tool for Incident Commanders
Nathan Schurr, Janusz Marecki, John P. Lewis, Milind Tambe, Paul Scerri |
AAAI | 2 |