A Formal Semantics for Brahms Presented by Richard Stocker In co-operation with Maarten Sierhuis, Louise Dennis, Clare Dixon and Michael Fisher

Introduction Applications for Human-Agent-Robot Teamwork are now becoming more evident especially in areas such as space exploration, home healthcare and pervasive systems. The critical nature of some of these scenarios suggest some form of formal verification is required, at least for the safety of the human counterparts. An Example specification that may need to be checked is: Three robots and two astronauts can together build a shelter within one hour

Introduction-Brahms In [3,1] a formal approach to the problem of human-agent (and so astronaut-robot) analysis was proposed. This involved the model-checking of Brahms models [6, 10,9]. Brahms is a simulation/modelling language in which complex human-agent work patterns can be described. Brahms is based on the concept of rational agents and the system continues to be successfully used within NASA for the sophisticated modelling of astronaut-robot planetary exploration teams [2, 8, 7].

Brahms Brahms is a modelling language designed to model human activity whereby rational agents are used to model humans. The key aspects of Brahms are activities workframes thoughtframes facts beliefs detectables time

An Example Scenario Scenario 1 Student: Alex Alex studies in the Library until hungry When hungry, Alex moves to a restaurant and eats When finished eating Alex returns to the Library to study Additionally Object clock is present

Semantic Notations

Agent’s become invoked Alex and the Clock are instructed to “start” Note: Presuming Alex currently active workframe

Running Workframes There are workframes for Alex and the Clock to run and the system is at the point of checking workframes.

Popping the stack Alex is also operating a workframe, one called wf_study. First element is an activity of time Alex’s first task is to notify scheduler of the time of his activity:

Alex had the shortest activity Alex detects his time is different from the schedulers and that his activity was the shortest.

Belief Updates Conclude statement for the clock updating its belief on the time and updating the facts

Communication Belief transference rule for communication:

Suspension Current workframe is suspended because a higher priority workframe is available

Conclusion Brahms is a simulation/modelling language used to describe human-agent-robot teamwork. By creating these formal semantics for Brahms we wish to be able to model check the semantics of a Brahms model using tools such as the Agent- Infrastructure-Layer (AIL) toolkit. Thereby providing us with a tool to formally verify human-agent-robot teamwork scenarios represented in the Brahms language.

References 1. R. H. Bordini, M. Fisher, and M. Sierhuis. Formal Verification of Human-Robot Teamwork, W. Clancey, M. Sierhuis, C. Kaskiris, and R. van Hoof. Advantages of Brahms for Specifying and Implementing a Multiagent Human-Robotic Exploration System, M. Fisher, R. H. Bordini, and M. Sierhuis. Analysing Human-Agent Teamwork, A. S. Rao and M. Georgeff. BDI Agents: from theory to practice, A. S. Rao and M. P. Georgeff. Modeling Agents within a BDI-Architecture., Apr M. Sierhuis. Modeling and Simulating Work Practice. BRAHMS: a multiagent modeling and simulation language for work system analysis and design, M. Sierhuis. Multiagent Modeling and Simulation in Human-Robot Mission Operations, M. Sierhuis, J. M. Bradshaw, A. Acquisti, R. V. Hoof, R. Jeffers, and A. Uszok. Human- Agent Teamwork and Adjustable Autonomy in Practice, M. Sierhuis andW. J. Clancey. Modeling and SimulatingWork Practice: A Human-Centered Method for Work Systems Design, R. van Hoof. Brahms website:

System Initiation System scheduler checks its rule to set all agents running

No Thoughframes Active Currently none of the objects or agent’s have any of their thoughtframes active.

Detectables also empty Agents and object now check their detectables but find they are also empty

Checking Repeat The clock object has selected its workframe but now has to check the repeat variable, which is set to “true”.

Scheduler’s turn Once all the agent’s have notified scheduler of their activity durations the scheduler can then decide the next time step to jump to i.e. current time plus the shortest activity time.

Skipping through Scenario then keeps cycling from thoughtframes to detectables to variables and then to workframes. Once the clock has finished performing a count down of the time passing by it performs a simple belief update which increases the number of hours by 1. The clock then performs a communication to Alex to inform him an hour has passed.

Communication Communication is modelled similarly to a primitive activity: It sends time take to send the communication to the scheduler Receives a time from the scheduler to subtract from the communications duration It is however different in the respect that when the communication part is finished it has a belief update attached which updates the beliefs of the agent or object receiving the message.

Skipping through Alex processes a thoughtframe every time the clock tells him the time has progressed an hour, this thoughtframe updates his belief that he has become more hungry i.e. Hunger = Hunger +1. Eventually his hunger rises to a threshold point which activates a guard on another workframe. This workframe tells him to go eat. This means now Alex has two workframes to chose from, his already active studying workframe and one to eat. The workframe to eat has higher priority so studying needs to be suspended.

Moving to the Restaurant One of the activities in the workframe to eat, is to move to the restaurant. Move activities are similar to communication activities. They use a primitive activity for the duration of travel and then immediately follow with belief updates, however move activities update the beliefs of agent and the environments beliefs (the facts). Once in the restaurant Alex will perform workframes to order food, eat the food and then return to the Library where he will pick up his suspended workframe to study.

Pre-Processing Agent/object’s initial beliefs are set Initial facts of the world are set Geography is created; distance between areas etc. is calculated Example Scenario; Agent Alex’s initial beliefs Alex.howHungry = 15 Alex.location = Library Alex.time = 0 Clock.time = 0 All agent/objects also start in a “finished” state

Check belief updates Alex has now finished an activity, so checks for any belief updates before finishing for the clock tick, but he has none.