Global learning of decision trees by an evolutionary algorithm. - Marek Kretowski; Marek Grzes (Information Processing and Security Systems, 2005)

Global Induction of Oblique Decision Trees: An Evolutionary Approach. - Marek Kretowski; Marek Grzes (Intelligent Information Systems, 2005)

Mixed Decision Trees: An Evolutionary Approach. - Marek Kretowski; Marek Grzes (DaWaK, 2006)

Evolutionary Learning of Linear Trees with Embedded Feature Selection. - Marek Kretowski; Marek Grzes (ICAISC, 2006)

Evolutionary Induction of Cost-Sensitive Decision Trees. - Marek Kretowski; Marek Grzes (ISMIS, 2006)

Evolutionary Induction of Decision Trees for Misclassification Cost Minimization. - Marek Kretowski; Marek Grzes (ICANNGA (1), 2007)

Evolutionary Induction of Mixed Decision Trees. - Marek Kretowski; Marek Grzes (Int. J. Data Warehous. Min., 2007)

Robustness Analysis of SARSA(lambda): Different Models of Reward and Initialisation. - Marek Grzes; Daniel Kudenko (AIMSA, 2008)

An Empirical Analysis of the Impact of Prioritised Sweeping on the DynaQ's Performance. - Marek Grzes; Daniel Kudenko (ICAISC, 2008)

Multigrid Reinforcement Learning with Reward Shaping. - Marek Grzes; Daniel Kudenko (ICANN (1), 2008)

Knowledge-Based Reinforcement Learning for Data Mining. - Daniel Kudenko; Marek Grzes (ADMI, 2009)

Reinforcement Learning in RoboCup KeepAway with Partial Observability. - Sam Devlin; Marek Grzes; Daniel Kudenko (IAT, 2009)

Improving Optimistic Exploration in Model-Free Reinforcement Learning. - Marek Grzes; Daniel Kudenko (ICANNGA, 2009)

Theoretical and Empirical Analysis of Reward Shaping in Reinforcement Learning. - Marek Grzes; Daniel Kudenko (ICMLA, 2009)

Reinforcement Learning with Reward Shaping and Mixed Resolution Function Approximation. - Marek Grzes; Daniel Kudenko (Int. J. Agent Technol. Syst., 2009)

PAC-MDP learning with knowledge-based admissible models. - Marek Grzes; Daniel Kudenko (AAMAS, 2010)

Online learning of shaping rewards in reinforcement learning. - Marek Grzes; Daniel Kudenko (Neural Networks, 2010)

Improving exploration in reinforcement learning through domain knowledge and parameter analysis. - Marek Grzes (2010)

Distributed Control of Situated Assistance in Large Domains with Many Tasks. - Jesse Hoey; Marek Grzes (ICAPS, 2011)

Multi-agent, reward shaping for RoboCup KeepAway. - Sam Devlin; Marek Grzes; Daniel Kudenko (AAMAS, 2011)

Efficient planning in R-max. - Marek Grzes; Jesse Hoey (AAMAS, 2011)

Multi-Test Decision Trees for Gene Expression Data Analysis. - Marcin Czajkowski; Marek Grzes; Marek Kretowski (SIIS, 2011)

An Empirical Study of Potential-Based Reward Shaping and Advice in Complex, Multi-Agent Systems. - Sam Devlin; Daniel Kudenko; Marek Grzes (Adv. Complex Syst., 2011)

Analysis of methods for solving MDPs. - Marek Grzes; Jesse Hoey (AAMAS, 2012)

Controller Compilation and Compression for Resource Constrained Applications. - Marek Grzes; Pascal Poupart; Jesse Hoey (ADT, 2013)

Isomorph-Free Branch and Bound Search for Finite State Controllers. - Marek Grzes; Pascal Poupart; Jesse Hoey (IJCAI, 2013)

On the convergence of techniques that improve value iteration. - Marek Grzes; Jesse Hoey (IJCNN, 2013)

POMDP planning and execution in an augmented space. - Marek Grzes; Pascal Poupart (AAMAS, 2014)

Multi-test decision tree and its application to microarray data classification. - Marcin Czajkowski; Marek Grzes; Marek Kretowski (Artif. Intell. Medicine, 2014)

Relational approach to knowledge engineering for POMDP-based assistance systems as a translation of a psychological model. - Marek Grzes; Jesse Hoey; Shehroz S. Khan; Alex Mihailidis; Stephen Czarnuch; Daniel Jackson 002; Andrew Monk (Int. J. Approx. Reason., 2014)

Incremental Policy Iteration with Guaranteed Escape from Local Optima in POMDP Planning. - Marek Grzes; Pascal Poupart (AAMAS, 2015)

The 2014 International Planning Competition: Progress and Trends. - Mauro Vallati; Lukás Chrpa; Marek Grzes; Thomas Leo McCluskey; Mark Roberts; Scott Sanner (AI Mag., 2015)

Energy Efficient Execution of POMDP Policies. - Marek Grzes; Pascal Poupart; Xiao Yang; Jesse Hoey (IEEE Trans. Cybern., 2015)

Estimating the Accuracy of Spectral Learning for HMMs. - Farhana Ferdousi Liza; Marek Grzes (AIMSA, 2016)

A Spectral Method that Worked Well in the SPiCe'16 Competition. - Farhana Ferdousi Liza; Marek Grzes (ICGI, 2016)

An Improved Crowdsourcing Based Evaluation Technique for Word Embedding Methods. - Farhana Ferdousi Liza; Marek Grzes (RepEval@ACL, 2016)

Reward Shaping in Episodic Reinforcement Learning. - Marek Grzes (AAMAS, 2017)

Improving Language Modelling with Noise Contrastive Estimation. - Farhana Ferdousi Liza; Marek Grzes (AAAI, 2018)

Reinforcement Learning using Augmented Neural Networks. - Jack Shannon; Marek Grzes (CoRR, 2018)

Self-adaptive artificial intelligence. - Rogério de Lemos; Marek Grzes (SEAMS@ICSE, 2019)

Comparing Explanations between Random Forests and Artificial Neural Networks. - Lee Harris; Marek Grzes (SMC, 2019)

SESAM at SemEval-2020 Task 8: Investigating the Relationship between Image and Text in Sentiment Analysis of Memes. - Lisa Bonheme; Marek Grzes (SemEval@COLING, 2020)

Realising Active Inference in Variational Message Passing: the Outcome-blind Certainty Seeker. - Théophile Champion; Marek Grzes; Howard Bowman (CoRR, 2021)

Realizing Active Inference in Variational Message Passing: The Outcome-Blind Certainty Seeker. - Théophile Champion; Marek Grzes; Howard Bowman (Neural Comput., 2021)

Training GPT-2 to represent two Romantic-era authors: challenges, evaluations and pitfalls. - Piotr Sawicki; Marek Grzes; Anna Jordanous; Dan Brown 001; Max Peeperkorn (ICCC, 2022)

How do Variational Autoencoders Learn? Insights from Representational Similarity. - Lisa Bonheme; Marek Grzes (CoRR, 2022)

Multi-Modal and Multi-Factor Branching Time Active Inference. - Théophile Champion; Marek Grzes; Howard Bowman (CoRR, 2022)

FONDUE: an algorithm to find the optimal dimensionality of the latent representations of variational autoencoders. - Lisa Bonheme; Marek Grzes (CoRR, 2022)

Crowd Score: A Method for the Evaluation of Jokes using Large Language Model AI Voters as Judges. - Fabrício Góes; Zisen Zhou; Piotr Sawicki; Marek Grzes; Daniel G. Brown 001 (CoRR, 2022)

Branching Time Active Inference with Bayesian Filtering. - Théophile Champion; Marek Grzes; Howard Bowman (Neural Comput., 2022)

Branching time active inference: Empirical study and complexity class analysis. - Théophile Champion; Howard Bowman; Marek Grzes (Neural Networks, 2022)

Branching Time Active Inference: The theory and its generality. - Théophile Champion; Lancelot Da Costa; Howard Bowman; Marek Grzes (Neural Networks, 2022)

Is GPT-4 Good Enough to Evaluate Jokes? - Fabrício Góes; Piotr Sawicki; Marek Grzes; Marco Volpe 001; Dan Brown 001 (ICCC, 2023)

Pushing GPT's Creativity to Its Limits: Alternative Uses and Torrance Tests. - Fabrício Góes; Piotr Sawicki; Marek Grzes; Marco Volpe 001; Jacob Watson (ICCC, 2023)

Bits of Grass: Does GPT already know how to write like Whitman? - Piotr Sawicki; Marek Grzes; Fabrício Góes; Dan Brown 001; Max Peeperkorn; Aisha Khatun (ICCC, 2023)

On the power of special-purpose GPT models to create and evaluate new poetry in old styles. - Piotr Sawicki; Marek Grzes; Fabrício Góes; Anna Jordanous; Dan Brown 001; Simona Paraskevopoulou; Max Peeperkorn; Aisha Khatun (ICCC, 2023)

The Polarised Regime of identifiable Variational Autoencoders. - Lisa Bonheme; Marek Grzes (Tiny Papers @ ICLR, 2023)

Posterior Collapse in Variational Gradient Origin Networks. - Peter Clapham; Marek Grzes (ICMLA, 2023)

Deconstructing deep active inference. - Théophile Champion; Marek Grzes; Lisa Bonheme; Howard Bowman (CoRR, 2023)

How good are variational autoencoders at transfer learning? - Lisa Bonheme; Marek Grzes (CoRR, 2023)

Be More Active! Understanding the Differences Between Mean and Sampled Representations of Variational Autoencoders. - Lisa Bonheme; Marek Grzes (J. Mach. Learn. Res., 2023)

Reframing the Expected Free Energy: Four Formulations and a Unification. - Théophile Champion; Howard Bowman; Dimitrije Markovic; Marek Grzes (CoRR, 2024)

Structure learning with Temporal Gaussian Mixture for model-based Reinforcement Learning. - Théophile Champion; Marek Grzes; Howard Bowman (CoRR, 2024)

Deconstructing Deep Active Inference: A Contrarian Information Gatherer. - Théophile Champion; Marek Grzes; Lisa Bonheme; Howard Bowman (Neural Comput., 2024)

Can Large Language Models Outperform Non-Experts in Poetry Evaluation? A Comparative Study Using the Consensual Assessment Technique. - Piotr Sawicki; Marek Grzes; Dan Brown 001; Fabrício Góes (CoRR, 2025)