# Clingo = ASP + Control: Preliminary Report

arXiv: https://arxiv.org/abs/1405.3694 · HTML: https://mlsanity.com/paper/1405.3694/

## Key facts

- Cited by 56 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 May 2014.

## Built on by (most cited first, 30 of 56)

- [RuleBert: Teaching Soft Rules to Pre-trained Language Models](https://mlsanity.com/paper/2109.13006/) (2021)
- [Learning MDL logic programs from noisy data](https://mlsanity.com/paper/2308.09393/) (2023)
- [AUTO-DISCERN: Autonomous Driving Using Common Sense Reasoning](https://mlsanity.com/paper/2110.13606/) (2021)
- [ReasoningFlow: Semantic Structure of Complex Reasoning Traces](https://mlsanity.com/paper/2506.02532/) (2025)
- [Rushing and Strolling among Answer Sets -- Navigation Made Easy](https://mlsanity.com/paper/2112.07596/) (2021)
- [Treewidth-aware Reductions of Normal ASP to SAT -- Is Normal ASP Harder than SAT after All?](https://mlsanity.com/paper/2210.03553/) (2022)
- [Learning logic programs by combining programs](https://mlsanity.com/paper/2206.01614/) (2022)
- [Efficient Knowledge Compilation Beyond Weighted Model Counting](https://mlsanity.com/paper/2205.07496/) (2022)
- [Modeling and Reasoning in Event Calculus using Goal-Directed Constraint Answer Set Programming](https://mlsanity.com/paper/2106.14566/) (2021)
- [Generating Explainable Rule Sets from Tree-Ensemble Learning Methods by Answer Set Programming](https://mlsanity.com/paper/2109.08290/) (2021)
- [Aspartix-V21](https://mlsanity.com/paper/2109.03166/) (2021)
- [HySTER: A Hybrid Spatio-Temporal Event Reasoner](https://mlsanity.com/paper/2101.06644/) (2021)
- [DiscASP: A Graph-based ASP System for Finding Relevant Consistent Concepts with Applications to Conversational Socialbots](https://mlsanity.com/paper/2109.08297/) (2021)
- [Process discovery on deviant traces and other stranger things](https://mlsanity.com/paper/2109.14883/) (2021)
- [On Model Reconciliation: How to Reconcile When Robot Does not Know Human's Model?](https://mlsanity.com/paper/2208.03091/) (2022)
- [Learning programs with magic values](https://mlsanity.com/paper/2208.03238/) (2022)
- [Relational program synthesis with numerical reasoning](https://mlsanity.com/paper/2210.00764/) (2022)
- [Trust, Accountability, and Autonomy in Knowledge Graph-based AI for Self-determination](https://mlsanity.com/paper/2310.19503/) (2023)
- [The Future of Intelligent Healthcare: A Systematic Analysis and Discussion on the Integration and Impact of Robots Using Large Language Models for Healthcare](https://mlsanity.com/paper/2411.03287/) (2024)
- [Counting and Reasoning with Plans](https://mlsanity.com/paper/2502.00145/) (2025)
- [Can LLMs Generate Good Stories? Insights and Challenges from a Narrative Planning Perspective](https://mlsanity.com/paper/2506.10161/) (2025)
- [grASP: A Graph Based ASP-Solver and Justification System](https://mlsanity.com/paper/2104.01190/) (2021)
- [Learning logic programs through divide, constrain, and conquer](https://mlsanity.com/paper/2109.07818/) (2021)
- [An Application of a Runtime Epistemic Probabilistic Event Calculus to Decision-making in e-Health Systems](https://mlsanity.com/paper/2209.13043/) (2022)
- [ASPER: Answer Set Programming Enhanced Neural Network Models for Joint Entity-Relation Extraction](https://mlsanity.com/paper/2305.15374/) (2023)
- [Assessing Drivers' Situation Awareness in Semi-Autonomous Vehicles: ASP based Characterisations of Driving Dynamics for Modelling Scene Interpretation and Projection](https://mlsanity.com/paper/2308.15895/) (2023)
- [Explainable Answer-set Programming](https://mlsanity.com/paper/2308.15901/) (2023)
- [Multi-step Inference over Unstructured Data](https://mlsanity.com/paper/2406.17987/) (2024)
- [Boolean Matrix Logic Programming on the GPU](https://mlsanity.com/paper/2408.10369/) (2024)
- [Generating Global and Local Explanations for Tree-Ensemble Learning Methods by Answer Set Programming](https://mlsanity.com/paper/2410.11000/) (2024)

## Abstract (arXiv)

We present the new ASP system clingo 4. Unlike its predecessors, being mere monolithic combinations of the grounder gringo with the solver clasp, the new clingo 4 series offers high-level constructs for realizing complex reasoning processes. Among others, such processes feature advanced forms of search, as in optimization or theory solving, or even interact with an environment, as in robotics or query-answering. Common to them is that the problem specification evolves during the reasoning process, either because data or constraints are added, deleted, or replaced. In fact, clingo 4 carries out such complex reasoning within a single integrated ASP grounding and solving process. This avoids redundancies in relaunching grounder and solver programs and benefits from the solver's learning capacities. clingo 4 accomplishes this by complementing ASP's declarative input language by control capacities expressed via the embedded scripting languages lua and python. On the declarative side, clingo 4 offers a new directive that allows for structuring logic programs into named and parameterizable subprograms. The grounding and integration of these subprograms into the solving process is completely modular and fully controllable from the procedural side, viz. the scripting languages. By strictly separating logic and control programs, clingo 4 also abolishes the need for dedicated systems for incremental and reactive reasoning, like iclingo and oclingo, respectively, and its flexibility goes well beyond the advanced yet still rigid solving processes of the latter.