{
    "componentChunkName": "component---src-layouts-default-js",
    "path": "/projects/modelling_decision_making/",
    "result": {"data":{"mdx":{"id":"0be3ea15-bf8b-5cb1-ae91-d6cce71cda92","body":"var _excluded = [\"components\"];\n\nfunction _extends() { _extends = Object.assign || function (target) { for (var i = 1; i < arguments.length; i++) { var source = arguments[i]; for (var key in source) { if (Object.prototype.hasOwnProperty.call(source, key)) { target[key] = source[key]; } } } return target; }; return _extends.apply(this, arguments); }\n\nfunction _objectWithoutProperties(source, excluded) { if (source == null) return {}; var target = _objectWithoutPropertiesLoose(source, excluded); var key, i; if (Object.getOwnPropertySymbols) { var sourceSymbolKeys = Object.getOwnPropertySymbols(source); for (i = 0; i < sourceSymbolKeys.length; i++) { key = sourceSymbolKeys[i]; if (excluded.indexOf(key) >= 0) continue; if (!Object.prototype.propertyIsEnumerable.call(source, key)) continue; target[key] = source[key]; } } return target; }\n\nfunction _objectWithoutPropertiesLoose(source, excluded) { if (source == null) return {}; var target = {}; var sourceKeys = Object.keys(source); var key, i; for (i = 0; i < sourceKeys.length; i++) { key = sourceKeys[i]; if (excluded.indexOf(key) >= 0) continue; target[key] = source[key]; } return target; }\n\n/* @jsxRuntime classic */\n\n/* @jsx mdx */\nvar _frontmatter = {\n  \"title\": \"Mathematical modelling for strategic decision-making in the future space economy\",\n  \"image_src\": \"/images/projects/strategic_dm.png\",\n  \"date\": \"2026-06-01T00:00:00.000Z\",\n  \"ongoing\": true,\n  \"categories\": [\"ai\"],\n  \"headline\": \"This project examines how policy, incentives, and coordination can support better strategic choices across emerging space-economy activities, from debris management to mega-constellations and space resource use.\"\n};\n\nvar makeShortcode = function makeShortcode(name) {\n  return function MDXDefaultShortcode(props) {\n    console.warn(\"Component \" + name + \" was not imported, exported, or provided by MDXProvider as global scope\");\n    return mdx(\"div\", props);\n  };\n};\n\nvar Image = makeShortcode(\"Image\");\nvar layoutProps = {\n  _frontmatter: _frontmatter\n};\nvar MDXLayout = \"wrapper\";\nreturn function MDXContent(_ref) {\n  var components = _ref.components,\n      props = _objectWithoutProperties(_ref, _excluded);\n\n  return mdx(MDXLayout, _extends({}, layoutProps, props, {\n    components: components,\n    mdxType: \"MDXLayout\"\n  }), mdx(Image, {\n    src: \"/images/projects/strategic_dm.png\",\n    align: \"right\",\n    width: \"350px\",\n    mdxType: \"Image\"\n  }), mdx(\"p\", null, \"As space becomes more commercially active, the main challenge is not only technical. It is also strategic: how do\\nwe encourage many independent actors to make choices that keep the orbital environment safe, usable, and economically\\nvaluable over the long term?\"), mdx(\"p\", null, \"This project studies strategic decision-making across the future space economy. Operators, infrastructure providers,\\nresource users, and public authorities do not act in isolation. Decisions about where to operate, which orbital slot\\nto occupy, which target to pursue, how much to invest in mitigation, or how access should be regulated can shift risks,\\ncosts, and opportunities across the wider system. For strategy makers, the core question is therefore how to design\\nincentives and rules that support collective outcomes without blocking innovation.\"), mdx(\"p\", null, \"This ongoing work builds on an earlier closed ACT study from 2015, \", mdx(\"a\", {\n    parentName: \"p\",\n    \"href\": \"/gsp/ACT/projects/gt_debris\"\n  }, \"Game theoretic analysis of the space debris\\nremoval dilemma\"), \", which first examined active debris removal as a strategic coordination problem.\\nThe present project explores a related class of applications, including debris management,\\nmega-constellation deployment, in-situ resource utilisation, and future orbital infrastructure.\"), mdx(\"p\", null, \"We use game theory and optimisation methods \", \"[1-5]\", \" to compare different governance options in a structured way.\\nIn practice, this means examining what happens when each actor follows its own interest, identifying where that leads\\nto congestion, avoidable risk, or inefficient use of shared resources, and testing which policy measures can improve\\nthe outcome. The work is intended to help decision-makers assess tools such as congestion fees, slot quotas,\\ndebris-mitigation incentives, access rules, royalty schemes, and priority policies.\"), mdx(\"p\", null, \"An important feature of the project is that the model used to compute optimal choices is validated against a\\nreal operational environment. For this, the project draws on ACT's open-source software tool \", mdx(\"a\", {\n    parentName: \"p\",\n    \"href\": \"/gsp/ACT/open_source/cascade\"\n  }, \"cascade\"), \",\\na C++/Python library for propagating large populations of orbiting objects while reliably and efficiently detecting\\nconjunction. Cascade is used to connect the strategic analysis with realistic orbital dynamics and conjunction computations.\\nThe analysis is thus not limited to economic behaviour in the abstract: it also takes account of the physical and\\nengineering realities that shape space missions.\"), mdx(\"p\", null, \"From a technical point of view, the work combines two modelling layers. The first represents competition among\\noperators when each actor pursues its own objective under mission and engineering constraints, and identifies the\\nresulting equilibrium. The second adds a regulator that chooses a policy in advance, then evaluates how operators\\nare likely to respond. In optimisation terms, this corresponds to non-cooperative equilibrium models on one side\\nand Stackelberg or bilevel policy design on the other \", \"[1-5]\", \". This allows the project to connect strategic behaviour,\\nregulatory design, and the physical realities of orbital operations in one framework.\"), mdx(\"p\", null, \"The framework can be applied across several parts of the future space economy. In mega-constellations, it can support\\ndecisions on how to reduce congestion and collision risk in low Earth orbit \", \"[6]\", \". In lunar and asteroid resource\\nactivities, it can help explore how competition over scarce locations or time-critical opportunities should be managed.\\nFor future orbital infrastructure, such as servicing platforms or data centres, it can clarify how choices about\\nlocation, access, spectrum, and jurisdiction may influence both market outcomes and the resilience of the wider\\nspace ecosystem.\"), mdx(Image, {\n    src: \"/images/projects/counterfactual_fee.png\",\n    align: \"center\",\n    width: \"750px\",\n    caption: \"Figure 1. Illustrative example: planner welfare, realised conjunctions, and revenue against a Pigouvian congestion fee \\u03C4. The bilevel program selects the welfare-maximising \\u03C4\\\\*; the right panel exhibits a Laffer-type revenue profile.\",\n    mdxType: \"Image\"\n  }), mdx(\"p\", null, \"The project also explores multi-agent reinforcement learning \", \"[7]\", \" as a way to examine how actors may adapt over time\\nwhen conditions are uncertain and behaviour is not perfectly predictable. This is useful for decision-makers because\\nreal-world actors do not always follow idealised assumptions: they learn, react, and change course as markets,\\ncosts, and regulations evolve.\"), mdx(\"p\", null, \"This research project is a collaboration between the ESA Advanced Concepts Team and CentraleSup\\xE9lec, Universit\\xE9 Paris-Saclay,\\nunder French National Research Agency project \", mdx(\"strong\", {\n    parentName: \"p\"\n  }, \"ANR-23-CE10-0006\"), \" (ANR-JCJC, 2024\\u20132027),\\n\", mdx(\"em\", {\n    parentName: \"p\"\n  }, \"Resilient and Sustainable Planning and Management of Future Space Industry Infrastructure\"), \", principal investigator Dr. Adam Abdin (CentraleSup\\xE9lec, Universit\\xE9 Paris-Saclay).\"), mdx(\"h2\", null, \"References\"), mdx(\"p\", null, \"[1]\", \" F. Facchinei and J.-S. Pang. \", mdx(\"em\", {\n    parentName: \"p\"\n  }, \"Finite-Dimensional Variational Inequalities and Complementarity Problems.\"), \" Springer, 2003.\"), mdx(\"p\", null, \"[2]\", \" T. Kleinert, M. Labb\\xE9, I. Ljubi\\u0107 and M. Schmidt. A survey on mixed-integer programming techniques in bilevel optimization. \", mdx(\"em\", {\n    parentName: \"p\"\n  }, \"EURO Journal on Computational Optimization\"), \", 9:100007, 2021.\"), mdx(\"p\", null, \"[3]\", \" S. Dempe and P. Mehlitz. Duality-based single-level reformulations of bilevel optimization problems. \", mdx(\"em\", {\n    parentName: \"p\"\n  }, \"Journal of Optimization Theory and Applications\"), \", 205(2):26, 2025.\"), mdx(\"p\", null, \"[4]\", \" Z. Feinstein and B. Rudloff. Characterizing and computing the set of Nash equilibria via vector optimization. \", mdx(\"em\", {\n    parentName: \"p\"\n  }, \"Operations Research\"), \", 72(5):2082\\u20132096, 2024.\"), mdx(\"p\", null, \"[5]\", \" Y. Beck, I. Ljubi\\u0107 and M. Schmidt. A survey on bilevel optimization under uncertainty. \", mdx(\"em\", {\n    parentName: \"p\"\n  }, \"European Journal of Operational Research\"), \", 311(2):401\\u2013426, 2023.\"), mdx(\"p\", null, \"[6]\", \" N. Adilov, P. J. Alexander and B. M. Cunningham. An economic analysis of Earth orbit pollution. \", mdx(\"em\", {\n    parentName: \"p\"\n  }, \"Environmental and Resource Economics\"), \", 60(1):81\\u201398, 2015.\"), mdx(\"p\", null, \"[7]\", \" K. Zhang, Z. Yang and T. Ba\\u015Far. Multi-agent reinforcement learning: a selective overview of theories and algorithms. In \", mdx(\"em\", {\n    parentName: \"p\"\n  }, \"Handbook of Reinforcement Learning and Control\"), \", pages 321\\u2013384, Springer, 2021.\"));\n}\n;\nMDXContent.isMDXComponent = true;","fields":{"slug":"/projects/modelling_decision_making/"},"frontmatter":{"title":"Mathematical modelling for strategic decision-making in the future space economy","pagetype":null,"categories":["ai"],"author":null,"institution":null,"banner":null,"banner_caption":null,"headline":"This project examines how policy, incentives, and coordination can support better strategic choices across emerging space-economy activities, from debris management to mega-constellations and space resource use.","image_src":"/images/projects/strategic_dm.png","date":"2026-06-01T00:00:00.000Z","time":null,"outcome":null}}},"pageContext":{"id":"0be3ea15-bf8b-5cb1-ae91-d6cce71cda92"}},
    "staticQueryHashes": ["2102389209","284332080","855417905"]}