Support for the Deployment of Ambient Intelligence Systems Managed by Cognitive Agents

Support for the Deployment
of Ambient Intelligence
Systems Managed by
Cognitive Agents
Laboratory for Advanced
Collaboration (LAC)
PUC-RJ
• 1. Federal Center for Technological Education (CEFET/RJ), Brazil
• 2. Fluminense Federal University (UFF), Brazil
Heder Dorneles 2
Carlos Eduardo Pantoja 1,2
José Viterbo 2
November 23th, 2017

OUTLINE 1. Introduction
2. Problem
3. Objective
4. Extending Jason Framework
5. Related Work
6. Conclusion
References

3Support for the Deployment of Ambient Intelligence Systems Managed by Cognitive Agents
1. INTRODUCTION: IoT
IoT

1. INTRODUCTION: AGENT APPROACH
• Agents [Wooldridge, 2000]
 agents are autonomous and cognitive entities
from artificial intelligence.

• Multi-Agent Systems [Wooldridge, 2009]
 Agents can collaborate with other agents and
they have common or conflicting goals. Besides
they are situated in an environment.

A
A C
MAS A

• Physical Agents [Matarić, 2007]:
 Hardware
 Sensors e Actuators
 Software (reasoning)
 Middleware

• Physical Agents [Matarić, 2007]:
 Hardware
 Sensors e Actuators
 Software (reasoning)
 Middleware
MAS

O Jason [Bordini et al., 2007] is a framework
for the development of Multi-Agent Systems.
O Jason is widely used in the field for the
development of Multi-Agent Systems and for
programming BDI software agents.
However, there was no implementation for
directly programming physical agents in
Jason.
1. INTRODUCTION: JASON
Jason by Gustave Moreau

1. INTRODUCTION: ARGO FOR JASON
ARGO [Pantoja et al., 2016] is a customized
architecture for a special kind of agent
responsible for controlling hardware devices
(ATMEGA, PIC, Intel, etc.):
• Javino [Lazarin and Pantoja, 2015]
 Interface for communication between
microcontrollers and high-level software
with error detection.
• Perceptions Filters [Stabile Jr e Sichman,
2015]
 Perceptions Filters reduce the amount of
information perceived by the agent at
runtime.
The Argo
by Lorenzo Costa

1. INTRODUCTION: ARGO FOR JASON
[Pantoja et al., 2016]

2. PROBLEM: MAS + IoT
A
A
A
A
A
A
A
A
[Pantoja and Viterbo, 2017]

2. PROBLEM: MAS + IoT
A
A
A
A
A
A
A
A
MAS 1 MAS 2

3. OBJECTIVE
IoT Middleware
A
A C
MAS

4. EXTENDING JASON: COMMUNICATION

A
A C
C
A
MAS A MAS B
Context Net
[Endler et al.,
2011]
4. EXTENDING JASON: COMMUNICATOR AGENT

4. EXTENDING JASON: REASONING CYCLE

4. EXTENDING JASON: COMMUNICATOR AGENT

4. EXTENDING JASON: MESSAGE FORMAT
.send(receiver, illocutionary forces, propositional content)

preamble field size sender
fffe 04
4 hex 2 hex up to 256 bytes
field size
2 hex
receiver
up to 256 bytes
field size
2 hex
force
up to 256 bytes
field size
2 hex
message
up to 256 bytes
kate 03 bob 07 achieve 08 Hello CN
.send(receiver, illocutionary forces, propositional content)
4. EXTENDING JASON: MESSAGE FORMAT

RECEIVERSENDER
Add the
preamble
Calculate the
size of all
fields
Mount the
message
Send the
message
using
ContexNet
Verify the
preamble
Is Ok?
Discard
message
Verify the size
of all fields
Is Ok?
Mount a
message
Start
sending a
message
Process it as
a Jason’s
Message
End of the
processyes
yes
no
no
4. EXTENDING JASON: MESSAGE PROCESS

RECEIVERSENDER
Add the
preamble
Calculate the
size of all
fields
Mount the
message
Verify the
preamble
Is Ok?
Discard
message
Verify the size
of all fields
Is Ok?
Mount a
message
Start
sending a
message
Process it as
a Jason’s
Message
End of the
processyes
yes
no
no
Send the
message
using
ContexNet

• ARGO Internal Actions:
• .sendOut(receiver, force, message)
• It defines a message to be sent to a mobile node in an IoT network.
4. EXTENDING JASON: INTERNAL ACTION

• ARGO Internal Actions:
• .sendOut(receiver, force, message)
• It defines a message to be sent to a mobile node in an IoT network.
Ex.: .sendOut ("788 b2b22−baa6 −4c61−b1bb− 33 01 cff1f5f878 ", achieve, decrease )
4. EXTENDING JASON: INTERNAL ACTION

4. EXTENDING JASON: EXAMPLE 1

4. EXTENDING JASON: EXAMPLE 2

4. EXTENDING JASON: EXAMPLE 3 (CEFET’s LAB)

5. RELATED WORK
Smart Homes
[Kazanavicius et al., 2009]
[Andrade et al. 2016]
[Martins and Meneguzzi 2013]
[Benta et al. ,2009]
Não Usa AOPL Específica
Jade [Bellifemine , 2004]
Jason [Bordini et al., 2007]
[Martins and Meneguzzi 2014]
[Conte et al. 2009]
[Lim et al. 2009]
[Sun et al. 2013]
[Hagras et al. 2004]
[Cook et al. 2003]
[Villarrubia et al. 2014]

This work extedend Jason framework for programming intelligent
agents using the ContextNet middleware for communication
and context management.
6. CONCLUSION AND FUTURE WORK

For future works...
This work extedend Jason framework for programming intelligent
agents using the ContextNet middleware for communication
and context management.

Symbiotic Relationships:
• Mutualism
• Commensalism
• Predation

REFERENCES
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