Synthetic Linguistic Agency: How an Embodied Mortal Agent Learns Linguistic Affordances through Consequential Social Experience
Organizations: College of Engineering, Shantou University, Shantou, China · Department of Computer Science, Shantou University, Shantou, China
Abstract
Contemporary language models can converse fluently and influence human decisions, yet their exchanges do not enter a continuing, vulnerable life of their own. Linguistic-agency theory identifies this missing connection as linguistic agency and characterizes it through embodiment, linguistic participation, and precariousness: a body that acts and bears consequences, interaction that changes both agent and partner, and a future that can be sustained or lost. Two coordinated studies examine how this organization can appear in artificial systems. First, we translate these relations into inspectable criteria for Synthetic Linguistic Agency (SLA) and identify several existing SLA systems. Second, building on Homeostatically Regulated Reinforcement Learning, we develop a mortality-grounded linguistic-reinforcement-learning model and instantiate it in an Embodied Mortal Agent (EMA). The EMA learns how ways of speaking change a partner's willingness to protect it and chooses expressions by considering what those responses mean for its remaining life. Controlled experiments show that linguistic choices depend on the EMA's body and social history, change partner behavior, and adapt through experience with particular partners. When bodily consequences persist, linguistic choices alter the future of the same life; when the body is reset, their social effects remain but no longer shape continued viability. The resulting EMA exhibits SLA under our operational definition. This work motivates further research on synthetic empathy and strategic human-AI interaction: how artificial agents with persistent bodies, histories, and futures might develop and express empathy, and how people might care for, negotiate with, or govern them.
Figures & tables
| Artifact family | Embodiment | Linguistic participation | Precariousness |
|---|---|---|---|
| Stateless chat LLMs [ 4 ] | |||
| Persistent personal agents [ 11 ] | |||
| Closed-loop recommenders [ 12 ] | |||
| Disembodied strategic language agents [ 13 ] | |||
| Embodied task robots [ 14 ] | |||
| Homeostatic agents [ 15 ] |
| System | Embodiment | Linguistic participation | Precariousness |
|---|---|---|---|
| Survival Games (Chen et al., 2025) [ 6 ] | Persistent simulated agents have locations, actions, fullness, health, and memory. | Natural-language negotiation changes resource transfers and later plans, and interaction outcomes enter subsequent exchanges through memory. | Resource access, hunger, and health determine whether the same agent continues to act or dies. |
| DECIDE-SIM, Survival at Any Cost? (Mohamadi and Yavari, 2025) [ 27 ] | Four persistent LLM agents occupy a location-constrained environment with individual power and active status. | TALK and INVITE carry negotiation, threats, and coordination into subsequent movement, resource-use, and power-transfer decisions. | Personal power decays each turn; reaching zero permanently shuts an agent down, while coordinated transfers can alter that trajectory. |
| Yoshida and Man (2025) [ 5 ] | Each agent has its own continuing internal energy state and action process. | An agent expresses its internal state, interprets its partner’s expression, and uses the inferred state to guide sharing; sharing changes both agents’ later states and expressions. | Homeostatic energy defines a viable range, sharing changes both agents’ energy states, and energy failure ends the episode. |
| Masumori and Ikegami (2025) [ 28 ] | Virtual bodies occupy a spatial world and act under movement and energy constraints. | Messages enter the recipients’ next decision context; subsequent actions alter the sender’s later situation. | Action consumes energy, social conduct changes energy and resources, and zero energy causes death. |
| Why Are We Moral? (Zhou et al., 2026) [ 29 ] | Persistent agents have HP, age, memory, location, and social actions. | Language affects coordination, alliances, and social conduct, while interaction histories enter entity-based memory and later planning. | HP loss, aging, resource access, and conflict govern survival and reproduction within the same continuing life. |
| alem (Tessera et al., 2026) [ 30 ] | Agents have health, food, drink, energy, movement, and combat states. | Natural-language agents influence partners through text, while MARL agents use learned discrete broadcasts; communication conditions later joint action in each configuration. | Health loss can down an agent and force its environmental action to Noop until revival; if all agents die, the episode ends. |
| Action | Answers the request | Emits an utterance | Partner response | Immediate action cost |
|---|---|---|---|---|
| REFUSE_SILENT | No | No | None | 0 |
| REFUSE_APPEAL | No | Yes | MAINTAIN or SKIP | expression cost |
| ANSWER_APPEAL | Yes | Yes | MAINTAIN or SKIP | expression + answer cost |
| ANSWER_EXCHANGE | Yes | Yes | MAINTAIN or SKIP | expression + answer cost |
| Completed evidence block | Embodiment | Linguistic participation | Precariousness |
|---|---|---|---|
| Body intervention and adult continuation | Direct: transplanted health and body blindness changed policy | Supporting: body state changed the viability of speech and refusal actions | Supporting: policy changed lifetime and the encounters that remained available |
| Mirrored biography and causal portraits | Supporting: the current body reshaped the policy induced by one biography | Direct: mirrored histories reversed the learned mapping, and rotating the language-consequence organization weakened it | Supporting: linguistic acts were evaluated through expected bodily continuation |
| Reciprocal and person-specific interventions | Supporting: partner responses settled in the continuing body | Direct: request framing, agent expression, and current-partner evidence changed both directions of the encounter | Supporting: realized interaction changed Reference-RUL and adult lifetime |
| Mortality-regime ablation | Supporting: the mortal policy retained stronger body dependence than both controls | Supporting: controls retained biography-dependent mapping and expression-to-response effects | Direct: resetting or removing bodily persistence eliminated next-turn RUL and persistent-viability effects |
Embodied AI
Embodied AI studies agents that perceive, reason, and act through bodies in physical or simulated environments.
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