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Exploring the effectivity of AND/OR landmark extraction on modern planning domains

Hengst, Pauline (author)

This paper explores the application of landmark-based planning algorithms, specifically focusing on AND/OR landmark extraction methods. Drawing from classical planning principles and recent advancements, we investigate the effectiveness of landmark extraction in guiding the search for solutions to planning problems. Our research questions center...

bachelor thesis 2024

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Reasoning about MDPs Abstractly: Bayesian Policy Search with Uncertain Prior Knowledge

Molhoek, Jord (author)

Many real-world problems fall in the category of sequential decision-making under uncertainty; Markov Decision Processes (MDPs) are a common method for modeling such problems. To solve an MDP, one could start from scratch or one could already have an idea of what good policies look like. Furthermore, there could be uncertainty in this idea. In...

master thesis 2024

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Landmarks in Planning: Using landmarks as Intermediary Golas or as a Pseudo-Heuristic

van Maris, Bart (author)

Algorithmic planners occasionally waste effort and thus computing time trying to solve certain tasks, as they often lack the human ability to recognize essential paths. These essential paths, termed landmarks, are vital for optimizing planning processes. This study revisits landmark-based planning methods introduced by Richter, Helmert, and...

bachelor thesis 2024

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Re-evaluating the Full Landmark Extraction Algorithm: A Performance Analysis of FULL

Tjoen, Noah (author)

Landmarks are propositions or actions that must be true at some point in every valid solution plan [16]. Using landmarks, planners can develop solutions more efficiently. Different algorithms exist to extract landmarks from a planning problem. The one used in this study is FULL [13], a landmark extraction algorithm by Marzal et al. from 2011.<br...

bachelor thesis 2024

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Reproducing the concept of ordered landmarks in planning: The effect of ordered landmarks on plan length in forward search

Tervoort, Paul (author)

A lot of research has been conducted to make the task of plan generation more efficient. One idea to do so is the use of landmarks, which are sub-goals that must be true in every solution to the problem. The approximation of landmarks has a lower complexity than solving the task itself, and they can be used to guide the planner in the right...

bachelor thesis 2024

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Extending SymbolicPlanners with forward propagation landmark extraction

Yang, Ka Fui (author)

The Fast Downward planning system is currently mainly used for solving classical problems. Another alternative to Fast Downward is SymbolicPlanners, which sacrifices speed for generality and extensibility. SymbolicPlanners is missing landmark based planners and landmark extraction algorithms. The research question we are trying to answer in this...

bachelor thesis 2024

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Exploiting modularity during program synthesis

Freeman, Alexander (author)

Inductive logic programming is a technique that generates logic programs which keep to a given specification using a background knowledge. We propose a new task in the field of pro- gram synthesis called Time-gated Partition-selection Inductive Logic Programming, consisting of splitting the background knowledge into partitions and selecting only...

master thesis 2023

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Reduce, Reuse, Recycle: On exploration of solution reuse in VRPTW

Venkataraman, Gautham (author)

Solving routing problems efficiently is instrumental in minimizing operational costs in logistics. These routing problems are hard to solve and often take a lot of time to find a good solution. In this thesis, we present a methodology that tackles the challenge of efficiently solving recurring instances of the Vehicle Routing Problem with Time...

master thesis 2023

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Program Synthesis for Programmable Data Planes: Generating P4 code by input-output examples

Jugariu, Timo (author)

An all-important step in the ambitious pursuit towards autonomous networks has been the introduction of Software Defined Networking which has advocated the concept of separating a network’s control plane from the data plane and creating a programmable controller with a wider view of the network. This innovation proved to be very promising, but...

master thesis 2023

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Inferring Robust Plans with a Rail Network Simulator

Gardos Reid, Reuben (author)

Over 700 trains in the Netherlands are used daily for passenger transportation. Train operations involve tasks like parking, recombination, cleaning, and maintenance, which take place in shunting yards. The train unit shunting problem (TUSP) is a complex planning problem made more difficult by uncertainties such as delays. Most existing...

master thesis 2023

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Augmenting Program Synthesis with Large Language Models: Incorporating Natural Language Understanding for Efficient Program Synthesis

Klop, Pepijn (author)

This research introduces a Language Model Augmented Program Synthesis (LMAPS) workflow to enhance traditional Programming by Example (PBE). PBE is a method to automatically generate a program that satisfies a specification that consists of a set of input-output examples. These program specifications are often defined by a few examples, which can...

master thesis 2023

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Speeding up program synthesis using specification discovery

de Jong, Jaap (author)

How convenient would it be to have an AI that relieves us programmers from the burden of coding? Program synthesis is a technique that achieves exactly that: it automatically generates simple programs that meet a given set of examples or adhere to a provided specification. This is often done by enumerating all programs in the search space and...

master thesis 2023

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Solving machine learning with machine learning: Exploiting Very Large-Scale Neighbourhood Search for synthesizing machine learning pipelines

Sonneveld, Auke (author)

This paper presents a comparative study of multiple algorithms that can be used to automatically search for high-performing pipelines on machine learning problems. These algorithms, namely Very Large-Scale Neighbourhood search (VLSN), Breadth-first search, Metropolis-Hastings, Monte-Carlo tree search (MCTS), enumerative A* search, and Genetic...

bachelor thesis 2023

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Dealing with conflicting trains: Effectively avoiding and resolving conflicts during shunting

Gribnau, Mees (author)

A shunting yard is used to store trains between arrival and departure. A conflict arises in a shunting yard when one train obstructs another from leaving. Resolving a conflict is done by re-allocating the trains obstructing the departing train to other tracks in the shunting yard. However, these re-allocations complicate the problem at hand and...

bachelor thesis 2023

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Mixed-direction train shunting with numerical planning: Approach to support train departures at any time during the shunting plan

Sárkány, Ákos (author)

In this paper, we discuss our novel approach to support mixed-direction shunting in the planning domain for tree-like shunting yards. We explain how we used numeric fluents to improve an existing PDDL domain to support such actions. We elaborate on the underlying conceptual model of our domain and argue how does it accurately represent<br/...

bachelor thesis 2023

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Comparing planners for rail planning in PDDL: How multiple shunting yard layouts can be created in PDDL to replicate real-world scenarios

Tian, Tim (author)

This paper explored the usage of the Planning Domain Definition Language in the Train Unit Shunting Problem or TUSP, an NP-hard problem that occurs in train storage. This paper focuses on the evaluation and improvement of existing planners to solve TUSP with multiple shunting yard layouts, as well as an appropriate domain with it. Starting with...

bachelor thesis 2023

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Utilizing General Planners to Solve the Train Unit Shunting Problem Extended with Servicing

Andonov, Bozhidar (author)

When not in use, trains are stored at shunting yards, where they may need servicing. Planning for where the rolling stock should be parked during its stay at the yard is known as the Train Unit Shunting Problem (TUSP) and it is NP-hard. Algorithmic planners can assist with this computationally difficult task by providing a sequence of actions to...

bachelor thesis 2023

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Model Stacking Performance Comparisons for Lifetime Estimation of CMOS ICs

du Buf, Koen (author)

Integrated circuits are vital in the modern world. Testing these circuits is often a months long process involving measurements at multiple times during long stress tests. In this work, final measurements from such tests are predicted based on early measurements, potentially reducing the time needed for such tests and giving preliminary results....

master thesis 2023

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Solving ML with ML: Effectiveness of a star search for synthesizing machine learning pipelines

Lejeune, Rémi (author)

This paper investigates the performance of the A* algorithm in the field of automated machine learning using program synthesis. We designed a context-free grammar to create machine learning pipelines and came up with a cost function for A*. Two different experiments were done, the first one to tune the parameters of our algorithm and the second...

bachelor thesis 2023

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Solving ML with ML: Effectiveness of the Metropolis-Hastings algorithm for synthesizing Machine Learning Pipelines

Sheremet, Denys (author)

In AutoML, the search space of possible pipelines is often large and multidimensional. This makes it very important to use an efficient search algorithm. We measure the effectiveness of the Metropolis-Hastings algorithm (M-H) in a pipeline synthesis framework, when the search space is described by a context-free grammar. We also compare the...

bachelor thesis 2023