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EXCITE / FIELDS OF POSSIBILITY

AUTONOMY / MAHCA

Individual agents.
Shared understanding.

Autonomous systems must do more than react individually. MAHCA explores world models for agents that perceive changing environments, anticipate interactions, and coordinate their actions.

WORLD-MODEL DEVELOPMENT

AUTONOMY / A SYSTEM IN MOTION
Local decisions. Collective behavior.

Explore an agent’s local view of the surrounding environment.

Local decisions. Collective behavior.DISCOVER THE DIRECTION
01

Understand the shared environment.

Represent the conditions and interactions that matter to each agent.

02

Anticipate the effect of an action.

Explore possible consequences before selecting a path.

03

Coordinate through change.

Investigate how local decisions contribute to a shared objective.

01 / FOCUSED POSSIBILITIES

Intelligence at the edge.
Coordination across the system.

Autonomy becomes a different problem when agents share a world. The research focus is how they represent that world, account for one another, and respond as conditions change.

COORDINATED DRONES

Explore the relationship between agent and team.

Study coordination questions for multiple drones operating toward a shared objective.

THE RESEARCH QUESTION

How can an agent’s local view inform collective behavior?

Local observationsAgent interactionsShared objectives

Connect individual decisions with the wider task.

CHANGING ENVIRONMENTS

Account for a world that moves.

Explore how routes and interactions could change when obstacles or operating conditions shift.

THE RESEARCH QUESTION

How should a change in the environment reshape the plan?

Environment statePossible routesOperating constraints

Evaluate responses to change in a simulation setting.

SHARED TASKS

Investigate coordination under uncertainty.

Examine how task choices, agent interactions, and incomplete observations affect a group’s behavior.

THE RESEARCH QUESTION

What information is needed to coordinate the next action?

Task prioritiesAvailable informationGroup behavior

Define coordination questions that can be tested.

02 / THE FOUNDATION

A model of the world.
A basis for the next action.

MAHCA is Excite’s coordinated autonomy world-model program. Its development explores the connection between local awareness, intelligent control, and collective behavior.

Explore our world models
01

Adaptive agents

Study responses to changing local conditions.

02

Predictive control

Explore how actions influence possible futures.

03

Distributed coordination

Investigate interactions across a group of agents.

03 / A CLOSER LOOK

Good questions.
Clear answers.

What is MAHCA?

MAHCA is Excite’s world-model development program for coordinated autonomy and interacting agents.

How is Excite bringing autonomous systems into the real world?

We are working with partners to deploy our autonomous systems in real-world environments. Powered by MAHCA, these systems combine coordinated decision-making with adaptive control for autonomous platforms.

How does this connect to Excite Quantum?

Autonomy focuses on coordination and decision-making. Excite Quantum explores physical signals and sensing: how the world becomes observations that can inform a model.

THE NEXT FRONTIER IS A SHARED ONE.

Build toward
coordinated intelligence.

Connect with Excite around autonomous systems, simulation, and research collaboration.

Discuss Autonomous Systems

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