Aug 2026· Zenodo (CERN European Organization for Nuclear Research)
Abstract
Large language model (LLM) agents have recently explored executable memory—compiling agent memory into code snippets that an external LLM interprets at inference time. We argue that this paradigm remains tied to a single architectural choice: the executor is an external model, the memory is a personal profile, and the code never participates in the agent's own memory economy. We present a cognitive simulation engine in which executable code is stored as unit-level memory entries and executed by a deterministic rule engine inside the simulation itself. A memory entry carrying an EXPR: prefix is a small program—an arithmetic expression over engine parameters and state variables—interpreted each generation; its result feeds directly into the unit's behavioral circuits. Code memory participates in the engine's memory economy: entries decay, are reinforced by hits, are evicted by capacity limits, and pass the same verification gates as any mechanism. Units acquire executable fragments by foraging, coupling energy gain with behavioral information transfer. Experiments show that (i) code memory measurably alters survival dynamics (extinction-count growth reduced by roughly 97% at threat 1.0); (ii) the survival benefit of code is stratified by strategy—decay reinforcement confers +15 generations at threat 1.5, healing reinforcement +10, while aggressive threat clearance confers no gain (clearing danger memories also clears the fear that drives defensive behavior); (iii) beyond a critical threat intensity (3.0) no code strategy confers benefit—a measured capability boundary; (iv) external trigger coupling: a unit's code can read an external trigger state (cognition) and, when the external signal is present, deterministically clear its own threat memories while writing an externally observable trace—with the external signal absent, the same code is inert, demonstrating that perception is a necessary component of the response; (v) cognitive code is acquired, not inherited: newly born units without the code fragment cannot perceive the external state, making cognition an evolvable individual trait; and (vi) when defensive and adversarial code coexist, an arms race emerges from primitive operations alone. We also report an unexpected semantics of negative-valued code, its diagnosis, and its redesign as a candidate inhibitory mechanism. The architecture points toward self-modifying systems in which memory, behavior, perception, and robustness converge on a single executable substrate.
Supporting data, adapters, predictions and code for the article *Low-Cost LoRA Fine-Tuning of Small Language Models for Multi-Step Arithmetic Reasoning* by Jake O'Grady, Asena Isik Gürhan, Chee Fong Ting and Effirul Ramlan (University of Galway). We generated 20,000 GSM8K-derived arithmetic problems with step-by-step s...
O'Grady, Jake, Gürhan, Asena Isik, Chee, Fong Ting et al.· Zenodo (CERN European Organi...· 465 citations
The results are packaged in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible, and the need to shorten time-to-market, by speeding up the development through low-precision engineering activities.
Carmine Giardino, Nicolò Paternoster, M. Unterkalmsteiner et al.· IEEE Transactions on Softwar...· 178 citations· ⚡14
Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models.
M. Unterkalmsteiner, P. Abrahamsson, Xiaofeng Wang et al.· e-Informatica Software Engin...· 157 citations· ⚡17
This study conducts a case survey study based on the secondary data of the major pivots happened in 49 software startups, and demonstrates that customer need pivot is the most common among all pivot types.
Sohaib Shahid Bajwa, Xiaofeng Wang, Anh Nguyen-Duc et al.· Empirical Software Engineeri...· 127 citations· ⚡15
The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.
Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al.· Journal of Systems and Softw...· 111 citations· ⚡8
This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.
Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al.· Journal of Systems and Softw...· 78 citations· ⚡6
Related blog posts
MIT News · Artificial Intelligence· news.mit.eduOct 18, 2026
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Microsoft Research Blog· microsoft.comOct 15, 2026
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.