DeepRAP: Deep Reasoning, Abstraction & Planning towards trustworthy Cognitive AI Systems

Description

DeepRAP: Deep Reasoning, Abstraction & Planning towards trustworthy Cognitive AI Systems Call: EIC Pathfinder Challenges 2026 Identifier: HORIZON-EIC-2026-PATHFINDERCHALLENGES-01-03 Call identifier: HORIZON-EIC-2026-PATHFINDERCHALLENGES-01 Kind: bando (topic) Status: aperto Opening date: 2026-07-22 Deadline: 2026-10-28 Deadline model: single-stage Type of action: HORIZON EIC Grants Budget: 2026: 96000000 EUR Contribution per project: 500000 - 4000000 EUR Expected grants: 8 Programme period: 2021 - 2027 Description Expected Impact: The resulting portfolio will not only advance the scientific state-of-the-art but also build a robust, interoperable, and application-driven community, positioning Europe at the forefront of trustworthy cognitive AI. It should also lay the foundations for future European leadership in safe, human-centric cognitive AI, supporting sovereignty and competitiveness in key sectors. It will support the ambitions of the AI Act [1] and the European approach to Artificial Intelligence [2]. Expected Outcome: Ambitious proposals put forward under this call will deliver: - Models and/or architectures that handle multimodal data and knowledge, uncertainty, and can be trained and deployed with constrained computational resources - Provable trustworthiness mechanisms ensuring explainability, transparency, fairness, risk evaluation, security and alignment with ethical and legal standards, including fundamental rights and the EU AI Act, and - Demonstrate the developed capabilities integrated in a cognitive AI system (reaching TRL4) performing complex real-world tasks (e.g., scientific discovery, decision support, problem solving) as well as simulations at a scale. In addition, proposals will: - Propose new methods and metrics for evaluating and certifying reasoning and trustworthiness in AI as well as the use of the computational resources - Follow the FAIR principles ensuring all data, models, and results are Findable, Accessible, Interoperable, and Reusable to maximise transparency, reproducibility, and impact, and - Develop synergies with EU initiatives such as TEFs (AI Testing and Experimentation Facilities) [3], eBrains [4], Resource for AI Science in Europe (RAISE) [5], AI-on-demand Platform (AIoD) [6] and the Quantum Flagship [7]. Portfolio approach The composition of the portfolio of projects to be funded under the DeepRAP Challenge will ensure comprehensive coverage across the following categories with a view to ensuring breadth and enabling synergies between the projects: - Category 1 – Cognitive Function Capability: Reasoning, abstraction, and planning should be covered by the selected portfolio. - Category 2 – Technological Approach: The selected projects are expected to use a variety of technological approaches, including but not limited to, neuro-symbolic AI, deep learning, reinforcement learning, and novel frameworks inspired by interdisciplinary fields, and - Category 3 – Use Case and Application Domain: The selected projects will cover a variety of real-world domains, such as industry, mobility, civil security, scientific discovery, health, cybersecurity, justice and human-robot interaction. The selected projects will also be assigned to lead and/or engage in portfolio activities centred on the following priorities: - Interoperability: Establishing common standards and protocols to ensure seamless alignment between projects - Benchmark Development: Co-creating a DeepRAP benchmark with shared tasks and an open evaluation platform for transparent assessment - Common Pilots: Delivering joint pilot demonstrations addressing complex real-world problems to showcase DeepRAP capabilities - Multiagent Integration: where feasible, combining project outcomes into modular, multiagent AI systems demonstrating collective reasoning and planning through structured interactions among multiple agents - Application Shaping: Defining impactful use cases and engaging stakeholders to guide the development and adoption of innovative cognitive AI systems, and - Ethical and Societal Alignment: Proactively addressing ethical, legal, and societal considerations, including fundamental rights, transparency, privacy, safety, and fairness of cognitive AI systems. Objective: Innovative ideas put forward under this Challenge must explore novel approaches, including combinations of existing techniques (i.e. neuro-symbolic AI), or the creation of entirely new frameworks that go beyond current, traditional, deep learning and reinforcement learning paradigms. These could be inspired by developments in diverse fields such as neuroscience, biology, physics, philosophy and more. The proposals should address one or more of the following cognitive capabilities: - Deep Reasoning: Moving beyond statistical pattern matching to support causal inference, logical reasoning, and context-aware or commonsense decision-making in complex, unstructured environments. This requires shifting from purely data-driven correlations to AI s

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Source: ec.europa.eu