AWI

class scml.scml2020.AWI(world, agent)

Bases: AgentWorldInterface

The Agent SCML2020World Interface for SCML2020 world.

This class contains all the methods needed to access the simulation to extract information which are divided into 5 groups:

Static World Information:

Information about the world and the agent that does not change over time. These include:

1. Market Information:

• n_products: Number of products in the production chain.

• n_processes: Number of processes in the production chain.

• n_competitors: Number of other factories on the same production level.

• all_suppliers: A list of all suppliers by product.

• all_consumers: A list of all consumers by product.

• catalog_prices: A list of the catalog prices (by product).

• inputs: Inputs to every manufacturing process.

• outputs: Outputs to every manufacturing process.

• is_system: Is the given system ID corresponding to a system agent?

• is_bankrupt: Is the given agent bankrupt (None asks about self)?

• current_step: Current simulation step (inherited from negmas.situated.AgentWorldInterface ).

• n_steps: Number of simulation steps (inherited from negmas.situated.AgentWorldInterface ).

• relative_time: fraction of the simulation completed (inherited from negmas.situated.AgentWorldInterface).

• settings: The system settings (inherited from negmas.situated.AgentWorldInterface ).

2. Agent Information:

• profile: Gives the agent profile including its production cost, number of production lines, input product index, mean of its delivery penalties, mean of its disposal costs, standard deviation of its shortfall penalties and standard deviation of its disposal costs. See OneShotProfile for full description. This information is private information and no other agent knows it.

• n_lines: the number of production lines in the factory (private information).

• is_first_level: Is the agent in the first production level (i.e. it is an input agent that buys the raw material).

• is_last_level: Is the agent in the last production level (i.e. it is an output agent that sells the final product).

• is_middle_level: Is the agent neither a first level nor a last level agent

• my_input_product: The input product to the factory controlled by the agent.

• my_output_product: The output product from the factory controlled by the agent.

• my_input_products: All input products of a factory controlled by the agent. Currently, it is always a list of one item. For future compatibility.

• my_output_products: All output products of a factory controlled by the agent. Currently, it is always a list of one item. For future compatibility.

• available_for_production: Returns the line-step slots available for production.

• level: The production level which is numerically the same as the input product.

• my_suppliers: A list of IDs for all suppliers to the agent (i.e. agents that can sell the input product of the agent).

• my_consumers: A list of IDs for all consumers to the agent (i.e. agents that can buy the output product of the agent).

• penalties_scale: The scale at which to calculate disposal cost/delivery penalties. “trading” and “catalog” mean trading and catalog prices. “unit” means the contract’s unit price while “none” means that disposal cost/shortfall penalty are absolute.

• n_input_negotiations: Number of negotiations with suppliers.

• n_output_negotiations: Number of negotiations with consumers.

• state: The full state of the agent ( FactoryState ).

• current_balance: The current balance of the agent

• current_inventory: The current inventory of the agent (quantity per product)

Dynamic World Information:

Information about the world and the agent that changes over time.

1. Market Information:

• trading_prices: The trading prices of all products. This information is only available if publish_trading_prices is set in the world.

• exogenous_contract_summary: A list of n_products tuples each giving the total quantity and average price of exogenous contracts for a product. This information is only available if publish_exogenous_summary is set in the world.

2. Other Agents’ Information:

• reports_of_agent: Gives all past financial reports of a given agent. See FinancialReport for details.

• reports_at_step: Gives all reports of all agents at a given step. See FinancialReport for details.

3. Current Negotiations Information:

• current_input_issues: The current issues for all negotiations to buy the input product of the agent. If the agent is at level zero, this will be empty.

• current_output_issues: The current issues for all negotiations to buy the output product of the agent. If the agent is at level n_products - 1, this will be empty.

4. Agent Information:

• spot_market_quantity: The quantity the agent bought from the spot market at

  a given step

• spot_market_loss: The spot market loss for the agent.

Actions:

1. Negotiation Control:

• request_negotiations: Requests a set of negotiations controlled by a single controller.

• request_negotiation: Requests a negotiation controlled by a single negotiator.

2. Production Control:

• schedule_production: Schedules production using one of the predefined scheduling strategies.

• order_production: Orders production directly for the current step.

• set_commands: Sets production commands directly on the factory.

• cancel_production: Cancels a scheduled production command.

Services (All inherited from negmas.situated.AgentWorldInterface):

• logdebug/loginfo/logwarning/logerror: Logs to the world log at the given log level.

• logdebug_agent/loginf_agnet/…: Logs to the agent specific log at the given log level.

• bb_query: Queries the bulletin-board.

• bb_read: Read a section of the bulletin-board.

Attributes Summary

accepted_negotiation_requests	A list of negotiation requests sent to this agent that are already accepted by it.
all_consumers	Returns a list of agent IDs for all consumers for every product
all_suppliers	Returns a list of agent IDs for all suppliers for every product
catalog_prices	Returns the catalog prices of all products
current_balance	Current balance of the agent
current_inventory	Current inventory of the agent
current_step	Current simulation step
default_signing_delay	rtype: int
exogenous_contract_summary	The exogenous contracts in the current step for all products
initialized	Was the agent initialized (i.e.
inputs	Returns the number of inputs to every production process
is_first_level	Whether this agent is in the first production level
is_last_level	Whether this agent is in the last production level
is_middle_level	Whether this agent is in neither in the first nor in the last level
level	The production level which is the index of the process for this factory (or the index of its input product)
my_consumers	Returns a list of IDs for all the agent's consumers (agents that can consume at least one product it may produce).
my_input_product	Returns a list of products that are inputs to at least one process the agent can run
my_input_products	Returns a list of products that are inputs to at least one process the agent can run
my_output_product	Returns a list of products that are outputs to at least one process the agent can run
my_output_products	Returns a list of products that are outputs to at least one process the agent can run
my_suppliers	Returns a list of IDs for all of the agent's suppliers (agents that can supply at least one product it may need).
n_competitors	Returns the number of factories/agents in the same production level
n_lines	The number of lines in the corresponding factory.
n_processes	Number of processes in the world
n_products	Number of products in the world
n_steps	Number of steps in a simulation
negotiation_requests	A list of the negotiation requests sent by this agent that are not yet accepted or rejected.
outputs	Returns the number of outputs to every production process
params	Returns the basic parameters of the world
profile	Gets the profile (static private information) associated with the agent
relative_time	Relative time of the simulation going from 0 to 1
requested_negotiations	The negotiations currently requested by the agent.
running_mechanism_dicts	The negotiations currently requested by the agent as a mapping from mechanism ID to RunningNegotiationInfo
running_negotiations	The negotiations currently requested by the agent.
settings
state	Receives the factory state
trading_prices	Returns the current trading prices of all products
unsigned_contracts	All contracts that are not yet signed.

Methods Summary

available_for_production(repeats[, step, ...])	Finds available times and lines for scheduling production.
bb_query(section, query[, query_keys])	Returns all records in the given section/sections of the bulletin-board that satisfy the query
bb_read(section, key)	Reads the value associated with given key from the bulletin board
bb_record(section, value[, key])	Records data in the given section of the bulletin board
bb_remove(section, *[, query, key, ...])	Removes a value or a set of values from the bulletin Board
cancel_production(step, line)	Cancels any production commands on that line at this step
execute(action[, callback])	Executes an action in the world simulation
is_bankrupt([aid])	Checks whether the agent is bankrupt
is_system(aid)	Checks whether an agent is a system agent or not
logdebug(msg)	Logs a WARNING message
logdebug_agent(msg)	Logs a WARNING message to the agent's log
logerror(msg)	Logs a WARNING message
logerror_agent(msg)	Logs a WARNING message to the agent's log
loginfo(msg)	Logs an INFO message
loginfo_agent(msg)	Logs an INFO message to the agent's log
logwarning(msg)	Logs a WARNING message
logwarning_agent(msg)	Logs a WARNING message to the agent's log
order_production(process, steps, lines)	Orders production of the given process
reports_at_step(step)	Returns a dictionary mapping agent ID to its financial report for the given time-step
reports_of_agent(aid)	Returns a dictionary mapping time-steps to financial reports of the given agent
request_negotiation(is_buy, product, ...[, ...])	Requests a negotiation
request_negotiation_about(issues, partners, ...)	Requests to start a negotiation with some other agents
request_negotiations(is_buy, product, ...[, ...])	Requests a negotiation
run_negotiation(issues, partners, negotiator)	Runs a negotiation until completion
run_negotiations(issues, partners, negotiators)	Requests to run a set of negotiations simultaneously.
schedule_production(process, repeats[, ...])	Orders the factory to run the given process at the given line at the given step
set_commands(commands[, step])	Sets the production commands for all lines in the given step
spot_market_loss(step)	The spot market loss of the agent at the given step.
spot_market_quantity(step)	The quantity bought by the agent from the spot market at the given step.

Attributes Documentation

accepted_negotiation_requests

A list of negotiation requests sent to this agent that are already accepted by it.

Remarks:

• These negotiations did not start yet as they are still not accepted by all partners. Once that happens, they will be moved to running_negotiations

Return type:

list[NegotiationRequestInfo]

all_consumers

Returns a list of agent IDs for all consumers for every product

Return type:

List[List[str]]

all_suppliers

Returns a list of agent IDs for all suppliers for every product

Return type:

List[List[str]]

catalog_prices

Returns the catalog prices of all products

Return type:

ndarray

current_balance

Current balance of the agent

current_inventory

Current inventory of the agent

current_step

Current simulation step

Return type:

int

default_signing_delay

Return type:

int

exogenous_contract_summary

The exogenous contracts in the current step for all products

Return type:

List[Tuple[int, int]]

Returns:

A list of tuples giving the total quantity and total price of all revealed exogenous contracts of all products at the current step.

initialized

Was the agent initialized (i.e. was init_() called)

Return type:

bool

inputs

Returns the number of inputs to every production process

Return type:

ndarray

is_first_level

Whether this agent is in the first production level

is_last_level

Whether this agent is in the last production level

is_middle_level

Whether this agent is in neither in the first nor in the last level

level

The production level which is the index of the process for this factory (or the index of its input product)

my_consumers

Returns a list of IDs for all the agent’s consumers (agents that can consume at least one product it may produce).

Remarks:

• If the agent have multiple output products, consumers of a specific product $p$ can be found using: self.all_consumers[p].

Return type:

List[str]

my_input_product

Returns a list of products that are inputs to at least one process the agent can run

Return type:

int

my_input_products

Returns a list of products that are inputs to at least one process the agent can run

Return type:

ndarray

my_output_product

Returns a list of products that are outputs to at least one process the agent can run

Return type:

int

my_output_products

Returns a list of products that are outputs to at least one process the agent can run

Return type:

ndarray

my_suppliers

Returns a list of IDs for all of the agent’s suppliers (agents that can supply at least one product it may need).

Remarks:

• If the agent have multiple input products, suppliers of a specific product $p$ can be found using: self.all_suppliers[p].

Return type:

List[str]

n_competitors

Returns the number of factories/agents in the same production level

Return type:

int

n_lines

The number of lines in the corresponding factory. You can read state to get this among other information

Return type:

int

n_processes

Number of processes in the world

Return type:

int

n_products

Number of products in the world

Return type:

int

n_steps

Number of steps in a simulation

Return type:

int

negotiation_requests

A list of the negotiation requests sent by this agent that are not yet accepted or rejected.

Remarks:

• These negotiations did not start yet as they are still not accepted by all partners. Once that happens, they will be moved to running_negotiations

Return type:

list[NegotiationRequestInfo]

outputs

Returns the number of outputs to every production process

Return type:

ndarray

params

Returns the basic parameters of the world

Return type:

dict[str, Any]

profile

Gets the profile (static private information) associated with the agent

Return type:

FactoryProfile

relative_time

Relative time of the simulation going from 0 to 1

Return type:

float

requested_negotiations

The negotiations currently requested by the agent.

Return type:

list[NegotiationRequestInfo]

Returns:

A list of negotiation request information objects (NegotiationRequestInfo)

running_mechanism_dicts

The negotiations currently requested by the agent as a mapping from mechanism ID to RunningNegotiationInfo

Return type:

dict[str, RunningNegotiationInfo]

Returns:

A list of negotiation information objects (RunningNegotiationInfo)

running_negotiations

The negotiations currently requested by the agent.

Return type:

list[RunningNegotiationInfo]

Returns:

A list of negotiation information objects (RunningNegotiationInfo)

settings

state

Receives the factory state

Return type:

FactoryState

trading_prices

Returns the current trading prices of all products

Return type:

ndarray

unsigned_contracts

All contracts that are not yet signed.

Return type:

list[Contract]

Methods Documentation

available_for_production(repeats, step=-1, line=-1, override=True, method='latest')

Finds available times and lines for scheduling production.

Parameters:

• repeats (int) – How many times to repeat the process

• step (Union[int, Tuple[int, int]]) – The simulation step or a range of steps. The special value ANY_STEP gives the factory the freedom to schedule production at any step in the present or future.

• line (int) – The production line. The special value ANY_LINE gives the factory the freedom to use any line

• override (bool) – Whether to override any existing commands at that line at that time.

• method (str) – When to schedule the command if step was set to a range. Options are latest, earliest, all

Return type:

Tuple[ndarray, ndarray]

Returns:

Tuple[np.ndarray, np.ndarray] The steps and lines at which production is scheduled.

Remarks:

• You cannot order production in the past or in the current step

• Ordering production, will automatically update inventory and balance for all simulation steps assuming that this production will be carried out. At the indicated step if production was not possible (due to insufficient funds or insufficient inventory of the input product), the predictions for the future will be corrected.

bb_query(section, query, query_keys=False)

Returns all records in the given section/sections of the bulletin-board that satisfy the query

Parameters:

• section (UnionType[str, list[str], None]) – Either a section name, a list of sections or None specifying ALL public sections (see remarks)

• query (Any) – The query which is USUALLY a dict with conditions on it when querying values and a RegExp when

• keys (querying) –

• query_keys – Whether the query is to be applied to the keys or values.

Returns:

value pairs giving all records that satisfied the given requirements.

Return type:

• A dictionary with key

Remarks:

• A public section is a section with a name that does not start with an underscore

• If a set of sections is given, and two records in different sections had the same key, only one of them will be returned

• Key queries use regular expressions and match from the beginning using the standard re.match function

bb_read(section, key)

Reads the value associated with given key from the bulletin board

Parameters:

• section (str) – section name

• key (str) – key

Return type:

Optional[Any]

Returns:

Content of that key in the bulletin-board

bb_record(section, value, key=None)

Records data in the given section of the bulletin board

Parameters:

• section (str) – section name (can contain subsections separated by ‘/’)

• key (Optional[str]) – The key

• value (Any) – The value

Return type:

None

bb_remove(section, *, query=None, key=None, query_keys=False, value=None)

Removes a value or a set of values from the bulletin Board

Parameters:

• section (UnionType[list[str], str, None]) – The section

• query (Optional[Any]) – the query to use to select what to remove

• key (Optional[str]) – the key to remove (no need to give a full query)

• query_keys (bool) – Whether to apply the query (if given) to keys or values

• value (Any) – Value to be removed

Returns:

Success of failure

Return type:

bool

cancel_production(step, line)

Cancels any production commands on that line at this step

Parameters:

• step (int) – The step to cancel production at (must be in the future).

• line (int) – The production line

Return type:

bool

Returns:

success/failure

Remarks:

• The step cannot be in the past or the current step. Cancellation can only be ordered for future steps

execute(action, callback=None)

Executes an action in the world simulation

Return type:

bool

is_bankrupt(aid=None)

Checks whether the agent is bankrupt

Parameters:

aid (Optional[str]) – Agent ID (None means self)

Return type:

bool

is_system(aid)

Checks whether an agent is a system agent or not

Parameters:

aid (str) – Agent ID

Return type:

bool

logdebug(msg)

Logs a WARNING message

Parameters:

msg (str) – The message to log

Returns:

Return type:

None

logdebug_agent(msg)

Logs a WARNING message to the agent’s log

Parameters:

msg (str) – The message to log

Returns:

Return type:

None

logerror(msg)

Logs a WARNING message

Parameters:

msg (str) – The message to log

Returns:

Return type:

None

logerror_agent(msg)

Logs a WARNING message to the agent’s log

Parameters:

msg (str) – The message to log

Returns:

Return type:

None

loginfo(msg)

Logs an INFO message

Parameters:

msg (str) – The message to log

Returns:

Return type:

None

loginfo_agent(msg)

Logs an INFO message to the agent’s log

Parameters:

msg (str) – The message to log

Returns:

Return type:

None

logwarning(msg)

Logs a WARNING message

Parameters:

msg (str) – The message to log

Returns:

Return type:

None

logwarning_agent(msg)

Logs a WARNING message to the agent’s log

Parameters:

msg (str) – The message to log

Returns:

Return type:

None

order_production(process, steps, lines)

Orders production of the given process

Parameters:

• process (int) – The process to run

• steps (ndarray) – The time steps to run the process at as an np.ndarray

• lines (ndarray) – The corresponding lines to run the process at

Remarks:

• len(steps) must equal len(lines)

• No checks are done in this function. It is expected to be used after calling available_for_production

Return type:

None

reports_at_step(step)

Returns a dictionary mapping agent ID to its financial report for the given time-step

Return type:

Dict[str, FinancialReport]

reports_of_agent(aid)

Returns a dictionary mapping time-steps to financial reports of the given agent

Return type:

Dict[int, FinancialReport]

request_negotiation(is_buy, product, quantity, unit_price, time, partner, negotiator, extra=None)

Requests a negotiation

Parameters:

• is_buy (bool) – If True the negotiation is about buying otherwise selling.

• product (int) – The product to negotiate about

• quantity (Union[int, Tuple[int, int]]) – The minimum and maximum quantities. Passing a single value q is equivalent to passing (q,q)

• unit_price (Union[int, Tuple[int, int]]) – The minimum and maximum unit prices. Passing a single value u is equivalent to passing (u,u)

• time (Union[int, Tuple[int, int]]) – The minimum and maximum delivery step. Passing a single value t is equivalent to passing (t,t)

• partner (str) – ID of the partner to negotiate with.

• negotiator (SAONegotiator) – The negotiator to use for this negotiation (if the partner accepted to negotiate)

• extra (Dict[str, Any]) – Extra information accessible through the negotiation annotation to the caller

Return type:

bool

Returns:

True if the partner accepted and the negotiation is ready to start

Remarks:

• All negotiations will use the following issues in order: quantity, time, unit_price

• Negotiations with bankrupt agents or on invalid products (see next point) will be automatically rejected

• Valid products for a factory are the following (any other products are not valid):

  1. Buying an input product (i.e. product $in$ my_input_products ) and an output product if the world settings allows it (see allow_buying_output)

  1. Selling an output product (i.e. product $in$ my_output_products ) and an input product if the world settings allows it (see allow_selling_input)

request_negotiation_about(issues, partners, req_id, roles=None, annotation=None, mechanism_name=None, mechanism_params=None, group=None)

Requests to start a negotiation with some other agents

Parameters:

• req_id (str) –

• issues (list[Issue]) – Negotiation issues

• annotation (Optional[dict[str, Any]]) – Extra information to be passed to the partners when asking them to join the negotiation

• partners (list[str]) – A list of partners to participate in the negotiation. Note that the caller itself may not be in this list which makes it possible for an agent to request a negotaition that it does not participate in. If that is not to be allowed in some world, override this method and explicitly check for these kinds of negotiations and return False. If partners is passed as a single string/Agent or as a list containing a single string/Agent, then he caller will be added at the beginning of the list. This will only be done if roles was passed as None.

• roles (Optional[list[str]]) – The roles of different partners. If None then each role for each partner will be None

• mechanism_name (Optional[str]) – Name of the mechanism to use. It must be one of the mechanism_names that are supported by the

• None (must also be) –

• my_role (then roles and) –

• None –

• mechanism_params (Optional[dict[str, Any]]) – A dict of parameters used to initialize the mechanism object

• group (Optional[str]) – An opational identifier for the group to which this negotiation belongs. It is not used by the system but is logged for debugging purposes. Moreover, the agent have access to it through its negotiations property.

Return type:

bool

Returns:

List[“Agent”] the list of partners who rejected the negotiation if any. If None then the negotiation was accepted. If empty then the negotiation was not started from the world manager

Remarks:

• The function will create a request ID that will be used in callbacks on_neg_request_accepted and

on_neg_request_rejected

request_negotiations(is_buy, product, quantity, unit_price, time, controller=None, negotiators=None, partners=None, extra=None, copy_partner_id=True)

Requests a negotiation

Parameters:

• is_buy (bool) – If True the negotiation is about buying otherwise selling.

• product (int) – The product to negotiate about

• quantity (Union[int, Tuple[int, int]]) – The minimum and maximum quantities. Passing a single value q is equivalent to passing (q,q)

• unit_price (Union[int, Tuple[int, int]]) – The minimum and maximum unit prices. Passing a single value u is equivalent to passing (u,u)

• time (Union[int, Tuple[int, int]]) – The minimum and maximum delivery step. Passing a single value t is equivalent to passing (t,t)

• controller (Optional[SAOController]) – The controller to manage the complete set of negotiations

• negotiators (List[Negotiator]) – An optional list of negotiators to use for negotiating with the given partners (in the same order).

• partners (List[str]) – ID of all the partners to negotiate with.

• extra (Dict[str, Any]) – Extra information accessible through the negotiation annotation to the caller

• copy_partner_id – If true, the partner ID will be copied to the negotiator ID

Return type:

bool

Returns:

True if the partner accepted and the negotiation is ready to start

Remarks:

• You can either use controller or negotiators. One of them must be None.

• All negotiations will use the following issues in order: quantity, time, unit_price

• Negotiations with bankrupt agents or on invalid products (see next point) will be automatically rejected

• Valid products for a factory are the following (any other products are not valid):

  1. Buying an input product (i.e. product $in$ my_input_products ) and an output product if the world settings allows it (see allow_buying_output)

  1. Selling an output product (i.e. product $in$ my_output_products ) and an input product if the world settings allows it (see allow_selling_input)

run_negotiation(issues, partners, negotiator, preferences=None, caller_role=None, roles=None, annotation=None, mechanism_name=None, mechanism_params=None)

Runs a negotiation until completion

Parameters:

• partners (list[str | Agent]) – A list of partners to participate in the negotiation. Note that the caller itself may not be in this list which makes it possible for an agent to request a negotaition that it does not participate in. If that is not to be allowed in some world, override this method and explicitly check for these kinds of negotiations and return False. If partners is passed as a single string/Agent or as a list containing a single string/Agent, then he caller will be added at the beginning of the list. This will only be done if roles was passed as None.

• negotiator (Negotiator) – The negotiator to be used in the negotiation

• preferences (Optional[Preferences]) – The preferences. Only needed if the negotiator does not already know it

• caller_role (Optional[str]) – The role of the caller in the negotiation

• issues (list[Issue]) – Negotiation issues

• annotation (Optional[dict[str, Any]]) – Extra information to be passed to the partners when asking them to join the negotiation

• partners – A list of partners to participate in the negotiation

• roles (Optional[list[str]]) – The roles of different partners. If None then each role for each partner will be None

• mechanism_name (Optional[str]) – Name of the mechanism to use. It must be one of the mechanism_names that are supported by the

• None (must also be) –

• my_role (then roles and) –

• None –

• mechanism_params (Optional[dict[str, Any]]) – A dict of parameters used to initialize the mechanism object

Return type:

Optional[tuple[Contract, NegotiatorMechanismInterface]]

Returns:

A Tuple of a contract and the nmi of the mechanism used to get it in case of success. None otherwise

run_negotiations(issues, partners, negotiators, preferences=None, caller_roles=None, roles=None, annotations=None, mechanism_names=None, mechanism_params=None, all_or_none=False)

Requests to run a set of negotiations simultaneously. Returns after all negotiations are run to completion

Parameters:

• partners (list[list[str | Agent]]) – A list of partners to participate in the negotiation. Note that the caller itself may not be in this list which makes it possible for an agent to request a negotaition that it does not participate in. If that is not to be allowed in some world, override this method and explicitly check for these kinds of negotiations and return False. If partners is passed as a single string/Agent or as a list containing a single string/Agent, then he caller will be added at the beginning of the list. This will only be done if roles was passed as None.

• issues (list[Issue] | list[list[Issue]]) – Negotiation issues

• negotiators (list[Negotiator]) – The negotiator to be used in the negotiation

• ufuns – The utility function. Only needed if the negotiator does not already know it

• caller_roles (Optional[list[str]]) – The role of the caller in the negotiation

• annotations (Optional[list[Optional[dict[str, Any]]]]) – Extra information to be passed to the partners when asking them to join the negotiation

• partners – A list of partners to participate in the negotiation

• roles (Optional[list[Optional[list[str]]]]) – The roles of different partners. If None then each role for each partner will be None

• mechanism_names (UnionType[str, list[str], None]) – Name of the mechanism to use. It must be one of the mechanism_names that are supported by the

• None (must also be) –

• my_role (then roles and) –

• None –

• mechanism_params (UnionType[dict[str, Any], list[dict[str, Any]], None]) – A dict of parameters used to initialize the mechanism object

• all_or_none (bool) – If true, either no negotiations will be started execpt if all partners accepted

Returns:

contract (None for failure) and nmi (The mechanism info [None if the corresponding partner refused to negotiation])

Return type:

A list of tuples each with two values

schedule_production(process, repeats, step=-1, line=-1, override=True, method='latest', partial_ok=False)

Orders the factory to run the given process at the given line at the given step

Parameters:

• process (int) – The process to run

• repeats (int) – How many times to repeat the process

• step (Union[int, Tuple[int, int]]) – The simulation step or a range of steps. The special value ANY_STEP gives the factory the freedom to schedule production at any step in the present or future.

• line (int) – The production line. The special value ANY_LINE gives the factory the freedom to use any line

• override (bool) – Whether to override existing production commands or not

• method (str) – When to schedule the command if step was set to a range. Options are latest, earliest

• partial_ok (bool) – If true, allows partial scheduling

Return type:

Tuple[ndarray, ndarray]

Returns:

Tuple[int, int] giving the steps and lines at which production is scheduled.

Remarks:

• The step cannot be in the past. Production can only be ordered for current and future steps

• ordering production of process -1 is equivalent of cancel_production only if both step and line are given

set_commands(commands, step=-1)

Sets the production commands for all lines in the given step

Parameters:

• commands (ndarray) – n_lines vector of commands. A command is either a process number to run or NO_COMMAND to keep the line idle

• step (int) – The step to set the commands at. If < 0, it means current step

Return type:

None

spot_market_loss(step)

The spot market loss of the agent at the given step.

Parameters:

step (Optional[int]) – The simulation step (day)

Remarks:

If step is None, the current step will be used

Return type:

int

spot_market_quantity(step)

The quantity bought by the agent from the spot market at the given step.

Parameters:

step (Optional[int]) – The simulation step (day)

Remarks:

If step is None, the current step will be used

Return type:

int