arXiv AI
Jun 24
Cost-Optimal Decision Diagrams for Stochastic Boolean Function Evaluation
arXiv:2606. 24672v1 Announce Type: new Abstract: In many decision-making scenarios, acquiring information incurs different costs.
Cost-Optimal Decision Diagrams for Stochastic Boolean Function Evaluation
In many decision-making scenarios, acquiring information incurs different costs. We consider the problem of constructing a deterministic evaluation strategy that minimizes the expected cost of evaluating a propositional formula under variable costs and a probability distribution over truth assignments.
Related stories
arXiv AI
Aug 12
Decision-Aware Approximation of Belief Functions for Evidential Combinatorial Optimization
arXiv:2608. 10650v1 Announce Type: new Abstract: Reducing the number of focal elements of a mass function is classically driven by an intrinsic distance, such as Jaccard or Jousselme, that keeps the approximation close to the original as a body of evidence.
arXiv Machine Learning
Sep 10
Fitting and Learning Basis-Restricted Propositional Formulas
arXiv:2609.08961v1 Announce Type: cross Abstract: For a finite set $O$ of Boolean functions, we consider the class of propositional formulas built using the functions in $O$ as connectives. We determ...
arXiv Machine Learning
Jun 25
Bellman-sufficient Information Complexity
arXiv:2606. 11171v4 Announce Type: replace Abstract: We develop Bellman-sufficient information complexity, a formal representation-level framework for sequential decision making.
arXiv Machine Learning
Aug 12
Simpler Logarithmic Approximation Algorithms for the Optimal Decision Tree and Adaptive Set Cover
arXiv:2604. 12036v3 Announce Type: replace-cross Abstract: We study a well-known task of constructing a decision tree identifying an unknown hypothesis from a given ground set of hypotheses under both the average- and worst-case cost.
arXiv AI
Jun 16
Runtime Analysis of Cartesian Genetic Programming in Evolving Boolean Functions
arXiv:2606. 15923v1 Announce Type: cross Abstract: Cartesian Genetic Programming (CGP) is among the practical and popular forms of Genetic Programming as it uses a graph-based representation of programs.
arXiv Machine Learning
Sep 22
Counting and Covering in Nearest-Neighbour Representations of Boolean Functions
arXiv:2609.23094v1 Announce Type: cross Abstract: We study the number of prototypes needed to represent Boolean functions by nearest-neighbour classification. There are two distinct settings: the pro...
arXiv Machine Learning
Jul 13
Information-Theoretic Bayesian Optimization for Bilevel Optimization Problems
arXiv:2509. 21725v3 Announce Type: replace Abstract: A bilevel optimization problem consists of two optimization problems nested as an upper- and a lower-level problem, in which the optimality of the lower-level problem defines a constraint for the upper-level problem.
arXiv Machine Learning
Jun 2
Statistical Guarantees for Reasoning Probes on Looped Boolean Circuits
arXiv:2602. 03970v3 Announce Type: replace-cross Abstract: We study the statistical behavior of reasoning probes in a stylized model of iterative computation inspired by neural algorithmic reasoning.
arXiv AI
Jun 24
The $\mathbf{P}$-Completeness of Inverted Index Traversal: On the Complexity of Evaluating Boolean Query DAGs
arXiv:2601. 18747v2 Announce Type: replace-cross Abstract: Modern AI agents increasingly rely on search infrastructure to execute complex, neuro-symbolic reasoning workflows.
arXiv Machine Learning
Jul 14
Precedence-Constrained Decision Trees and Coverings
arXiv:2602. 21312v4 Announce Type: replace-cross Abstract: This work considers a number of optimization problems and reductive relations between them.
arXiv AI
Aug 6
Capability-Gated Planning: Cost-to-Goal Discovery and the Limits of Myopic Experiment Selection
arXiv:2608. 05085v1 Announce Type: cross Abstract: Systems that automate scientific discovery must repeatedly decide which experiment to run, which hypothesis to test, which tool to build, and when to stop.